answered: 1 page  summary each article  1 question each relates to article  Contents lists available at Scie

1 page 

summary each article 

1 question each relates to article 

Contents lists available at ScienceDirect

Psychiatry Research

journal homepage: www.elsevier.com/locate/psychres

Review article

PTSD symptoms in healthcare workers facing the three coronavirus
outbreaks: What can we expect after the COVID-19 pandemic

Claudia Carmassia, Claudia Foghia, Valerio Dell’Ostea,b,⁎, Annalisa Cordonea,
Carlo Antonio Bertellonia, Eric Buic, Liliana Dell’Ossoa

a Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
b Department of Biotechnology Chemistry and Pharmacy, University of Siena, Siena, Italy
c Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

A R T I C L E I N F O

Keywords:
Corona
Mental health
Nurses
Physicians
Psychological distress
Stress

A B S T R A C T

The COronaVIrus Disease-19 (COVID-19) pandemic has highlighted the critical need to focus on its impact on
the mental health of Healthcare Workers (HCWs) involved in the response to this emergency. It has been con-
sistently shown that a high proportion of HCWs is at greater risk for developing Posttraumatic Stress Disorder
(PTSD) and Posttraumatic Stress Symptoms (PTSS). The present study systematic reviewed studies conducted in
the context of the three major Coronavirus outbreaks of the last two decades to investigate risk and resilience
factors for PTSD and PTSS in HCWs. Nineteen studies on the SARS 2003 outbreak, two on the MERS 2012
outbreak and three on the COVID-19 ongoing outbreak were included. Some variables were found to be of
particular relevance as risk factors as well as resilience factors, including exposure level, working role, years of
work experience, social and work support, job organization, quarantine, age, gender, marital status, and coping
styles. It will be critical to account for these factors when planning effective intervention strategies, to enhance
the resilience and reduce the risk of adverse mental health outcomes among HCWs facing the current COVID-19
pandemic.

1. Introduction

The outbreak of Corona Virus Disease-19 (COVID) that emerged in
December 2019 in Wuhan (China), quickly spread outside of China,
leading the World Health Organization (WHO) Emergency Committee
to declare a Public Health Emergency of International Concern (PHEIC)
on January 30th 2020 (Nishiura, 2020), and a pandemic on March 11,
2020. The SARS-CoV2 – the virus responsible for COVID-19 – was
isolated by 7th January 2020, and belongs to the same viral family as
the coronavirus syndrome (SARS-CoV) and the Middle East respiratory
coronavirus syndrome (MERS-CoV). Both of these coronavirus-based
respiratory syndromes infected over 10,000 cases in the past two dec-
ades, with overall mortality rates as high as 11% and 35%, respectively
(Peeri et al., al.,2020; de Wit et al., 2016; Leung et al., 2004;
WHO, 2004). Compared to the Severe Acute Respiratory Syndrome
(SARS) and the Middle East Respiratory Syndrome (MERS), the Corona
Virus Disease-19 (COVID-19) has a greater transmission rate but a
lower, though still significant, fatality rate (Peeri et al., 2020;
Huang et al., 2020). To date, with more than 14 million infected
worldwide and a spread that is far from being contained, investigating

the psychological impact of this pandemic on healthcare workers
(HCWs) including physicians and nurses, has become increasingly im-
portant.

In the last two decades, first responders’ mental health outcomes has
been the focus of increasing attention, particularly in the aftermath of
September 11 2001, terrorist attacks that shed light on the risks they
are exposed to when operating in emergency settings, as they may be
affected by physical and mental disorders, such as burnout and post-
traumatic stress disorder (PTSD) (Perlman et al., 2011; Carmassi et al.,
2016, 2018; Martin et al., 2017). The DSM-5 (APA, 2013) indicates that
“experiencing repeated or extreme exposure to aversive details of the trau-
matic event(s)” can be considered as potentially traumatic events (cri-
terion A4: e.g. first responders collecting human remains, police officers
repeatedly exposed to details of child abuse).

Healthcare Workers (HCWs) in emergency care settings are parti-
cularly at risk for PTSD because of the highly stressful work-related
situations they are exposed to, that include: management of critical
medical situations, caring for severely traumatized people, frequent
witnessing of death and trauma, operating in crowded settings, inter-
rupted circadian rhythms due to shift work) (Figley, 1995; Crabbe et al.,

https://doi.org/10.1016/j.psychres.2020.113312
Received 1 May 2020; Received in revised form 18 July 2020; Accepted 18 July 2020

⁎ Corresponding author at: Department of Clinical and Experimental Medicine, University of Pisa, Via Roma 67, 56100 Pisa, Italy.
E-mail address: [email protected] (V. Dell’Oste).

Psychiatry Research 292 (2020) 113312

Available online 20 July 2020
0165-1781/ © 2020 Elsevier B.V. All rights reserved.

T

2004; Cieslak et al., 2014; Berger et al., 2012; Hegg-Deloye et al., 2013;
Garbern et al., 2016). PTSD rates have been reported to range from 10
to about 20% (Grevin, 1996; Clohessy and Ehlers, 1999; Robertson and
Perry, 2010; DeLucia et al., 2019), with even higher PTSD rates (8% to
30%) among Intensive Care Unit (ICU) staff, (Mealer et al., 2009;
Karanikola et al., 2015; Machado et al., 2018).

Although most individuals prove to be resilient after being exposed
to a traumatic event (Bonanno et al., 2007), several risk factors may
compromise the effectiveness of adaptation, including prior psychiatric
history, female sex, lack of social support (Brewin et al., 1999;
Ozer et al., 2003; Carmassi et al., 2020a, 2020b), having young children
(Yehuda et al., 2015; Bryant 2019); experiencing feelings of help-
lessness during the trauma or intensity of emotions when exposed (i.e.,
anger, peritraumatic distress) (Vance et al., 2018; Carmassi et al.,
2017). On the other hand, resilience, defined as the capacity to react to
stress in a healthy way through which goals are achieved at a minimal
psychological and physical cost (Epstein and Krasner, 2013), plays a
key role in mitigating the impact of traumatic events and hence redu-
cing PTSS, enhancing at the same time the quality of care (Wrenn et al.,
2011; Ager et al., 2012; Haber et al., 2013; McGarry et al., 2013;
Craun and Bourke, 2014; Hamid and Musa, 2017; Colville et al., 2017;
Cleary et al., 2018; Winkel et al., 2019).

This interplay of risk and resilience factors becomes even more
complex and challenging when applied in the context of an infectious
epidemic. This statement is first supported by the fact that, as previous
studies outlined, during epidemics a high percentage of HCWs, (up to 1
in 6 of those providing care to affected patients), develops significant
stress symptoms (Lu et al., 2006; McAlonan et al., 2007) It is worth
considering that in epidemic contexts HCWs are first in line facing the
clinical challenges intrinsically linked to the course of the disease while
under the constant personal threat of being infected or representing a
source of infection.

The current COVID-19 pandemic is characterized by some relevant
features that increase the risk for PTSD among HCWs addressing the
emergency, such as the unprecedented numbers of critically ill patients,
with an often unpredictable course of the disease, high mortality rates
and lack of effective treatment, or treatment guidelines (Wang, 2020;
Peeri et al., 2020). Thus, the burden of the current outbreak on
healthcare providers deserves the closest attention, as it is extremely
likely that health care workers involved in the diagnosis, treatment and
care of patients with COVID-19 are at risk of developing psychological
distress and other mental health symptoms (Bao et al., 2020; Lai et al.,
2020; Carmassi et al., 2020c)

The aim of the present paper is therefore to systematically review
the studies investigating the potential risk and resilience factors for the
development of PTSD symptoms in HCWs who faced the two major
Coronavirus outbreaks that occurred worldwide in the last two decades,
namely the SARS and the MERS, as well as the ongoing COVID-19
pandemic, in order to outline effective measures to reduce the HCWs’
psychiatric burden during the current crisis affecting healthcare sys-
tems all over the world.

2. Methods

2.1. Search strategy

We reviewed articles indexed in the electronic database PubMed
until 20th April 2020. No time limit was set in regard to the year of
publication. The search terms were combined with the Boolean op-
erator as follows: “(Post-traumatic stress OR Post-traumatic stress dis-
order OR Post-traumatic stress symptoms OR PTSD OR PTSS) AND
(Severe Acute Respiratory Syndrome OR SARS OR Middle East
Respiratory Syndrome OR MERS OR Corona Virus Disease 19 OR
COVID-19 OR Coronavirus)”. Furthermore, relevant articles were ex-
tracted from the references section of the manuscripts found in the
initial search, to complete our search.

2.2. Eligibility criteria

We included articles that met the following inclusion criteria: ori-
ginal studies on humans investigating possible risk and/or resilience
factors for PTSD symptoms in HCWs facing the coronavirus outbreaks
of SARS, MERS and COVID-19. Articles in print or published ahead of
print were accepted. The exclusion criteria were: (a) studies involving
general population samples that did not consider a sub-sample of
HCWs; (b) studies examining other mental health symptoms but not
PTSS; (c) studies assessing PTSS but not considering potential risk and
resilience factors; (d) literature reviews; (e) full text not available; (f)
not available in English.

2.3. Study selection

The first author screened each study for eligibility by reading the
title and abstract. Any uncertainties about eligibility were clarified
through discussion among all authors. Decisions for inclusion or ex-
clusion are summarized in a flowchart according to PRISMA re-
commendations, usually used to conduct meta-analyses and systematic
reviews of randomized clinical trials, but that have also been used for
other types of systematic reviews such as our present one (Moher et al.,
2009).

3. Results

3.1. Process of study selection

The study selection process is outlined in a flow-chart (Fig. 1). The
electronic database search returned 263 publications. Following a
preliminary screening of the titles and abstracts, 47 articles were con-
sidered of potential relevance, their eligibility was assessed by means of
a full text examination. Twenty-four of these studies, published be-
tween 2004 and 2020, were included in this review. The main reasons
for study exclusion were: the absence of a HCW sample or sub-sample,
the lack of data regarding PTSS and/or about possible risk or resilience
factors related to psychopathology.

3.2. Characteristics of included studies

The key characteristics of the studies included are summarized in
Table 1. All retrieved studies were published between January 2004
and April 2020. Nineteen studies were on the SARS 2003 outbreak, two
on the MERS 2012 outbreak, and three on the ongoing Covid-19 out-
break. Nine studies were on a mixed population in which HCWs re-
presented a sub-sample (Bai et al., 2004; Chong et al., 2004;
Kwek et al., 2006; Reynolds et al., 2007; Lancee et al., 2008; Wu et al.,
2009; Mak et al., 2010; Wing and Leung, 2012; Li et al., 2020) while all
other studies included HCWs only. Finally, five studies included spe-
cifically survivors from the infection (Kwek et al., 2006; Lee et al.,
2007; Mak et al., 2010; Wing and Leung, 2012; Ho et al., 2005).

3.3. PTSD and PTSS risk factors in HCWs facing the coronavirus outbreaks

3.3.1. Level of exposure
Ten studies (Chong et al., 2004; Maunder et al., 2004; Lin et al.,

2007; Su et al., 2007; Styra et al., 2008; Wu et al., 2009; Lee et al.,
2018; Lai et al., 2020; Kang et al., 2020; Jung et al., 2020) highlighted
the role of exposure level, such as working in high-risk wards or in
front-line settings during the Coronavirus outbreaks, as the major risk
factor for developing PTSS and PTSD. Particularly, they pointed out the
relevance of perceived threat for health and life and the experienced
feelings of vulnerability as mediating factors. Most of these studies re-
ported on the 2003 SARS outbreak. Lin et al. (2007) showed higher
rates of PTSD (21,7%) among 66 emergency department staff compared
to 26 HCWs of non-emergency departments (i.e., psychiatric ward,

C. Carmassi, et al. Psychiatry Research 292 (2020) 113312

2

13%). Wu et al. (2009) investigated a sample of 549 HCWs in Beijing
(China), including administrative staff, finding 2 to 3 times higher PTSS
rates among respondents who worked in high-risk locations and per-
ceived high SARS-related risks, beside an increased risk for subsequent
alcohol abuse/dependence. This latter resulted significantly related
with hyper-arousal symptoms. A further study in Toronto (Styra et al.,
2008) confirmed the impact of operating in a high-risk unit, and first
reported that caring for only one SARS patient was related to a higher
risk than caring for multiple SARS patients. A recent study on 147
nurses who worked in MERS units during the outbreak found higher
PTSD rates among emergency HCWs than among non-emergency ones
(Jung et al., 2020). To date, two studies have explored this issue in the
COVID-19 pandemic. Li et al. (2020) found among 526 nurses, that
those who worked on the frontline appeared to be less prone to de-
veloping PTSS compared to second-line ones; conversely
Kang et al. (2020) in a large study on 994 HCWs in Wuhan reported the
exposure level to infected people, more broadly including colleagues,
relatives or friends, to be a risk factor for mental health problems, in-
cluding PTSS.

3.3.2. Occupational role
Five studies, four on the SARS epidemic and one on the COVID-19

pandemic, highlighted the occupational role as a major risk factor for
PTSD or PTSS in Coronavirus outbreaks. Maunder et al. (2004) found
on a sample of 1557 HCWs collected in Toronto, higher PTSS rates
among nurses and explained this finding by means of the longer contact
and higher exposure to patients of the nursing staff. A study on 96
emergency HCWs, assessed six months after the 2003 SARS outbreak,
revealed a greater burden of PTSS among nurses than among physicians
(Tham et al., 2004). A further study by Phua et al. (2005) confirmed
this finding in a sample of 99 HCWs. Finally, a most recent study on
1257 hospital physicians and nurses caring for COVID-19 patients
reached the same conclusion (Lai et al., 2020).

3.3.3. Age and gender
Three studies on the SARS outbreak and one on the COVID-19

pandemic reported that younger HCWs had a greater risk of developing
PTSS (Sim et al., 2004; Su et al., 2007; Wu et al., 2009). From a wider
perspective, further studies pointed out an association between fewer
years of work experience and an increased PTSS risk in HCWs, as de-
scribed in two SARS studies (Chong et al., 2004; Lancee et al., 2008)
and in one COVID-19 study (Lai et al., 2020). As far as gender is

concerned, while one recent study on COVID-19 reported a higher risk
for the female HCWs, a previous study involving 1257 HCWs in a ter-
tiary hospital affected by SARS found an increased risk of PTSS among
males (Chong et al., 2004).

3.3.4. Marital status
Three studies focused on the relevance of marital status, two of

which referred to the SARS outbreaks and one to the current COVID-19
pandemic. Chan and Huak (2004) in a study on 661 HCWs in Singapore
showed that those who were not married were more adversely affected
than married ones. In contrast, a further study in Singapore (Sim et al.,
2004) found a positive association between post-traumatic morbidities
and being married. Likewise, a recent case control study on HCWs fa-
cing the COVID-19 pandemic showed that married, divorced or wi-
dowed operators reported higher scores in vicarious traumatization
symptoms compared to unmarried HCWs (Li et al., 2020).

3.3.5. Quarantine, isolation and stigma
Three SARS studies on Chinese hospital staff members (Bai et al.,

2004; Reynolds et al., 2007; Wu et al., 2009) and one on the MERS
outbreak (Lee et al., 2018) consistently reported high levels of PTSS
among HCWs who had been quarantined. More specifically,
Bai et al. (2004) examining 338 HCWs in an East Taiwan hospital found
that 5% of them suffered from acute stress disorder, with quarantine
being the most frequently associated factor, and a further 20% felt
stigmatized and rejected in their neighborhood because of their hospital
work, with also 9% reporting reluctance to work and/or considering
quitting their job. Similar findings emerged from a Canadian SARS
study on 1057 subjects (Reynolds et al., 2007), in which quarantined
HCWs reported more PTSS than non-HCWs quarantined individuals.
Moreover, in a study on MERS outbreak, Lee et al. (2018) assessed PTSS
experienced by 359 university HCWs who cared for infected patients,
observing that quarantined HCWs had a higher risk of developing PTSS
which persisted over time, particularly sleep and numbness-related
symptoms. More in general, social isolation and separation from family
was found to be associated with higher rates of PTSS in SARS outbreak,
as well as having friends or close relatives with the infection
(Maunder et al., 2004; Chong et al., 2004; Wu et al., 2009).

3.3.6. Previous psychiatric disorders
Three studies on SARS have stressed the presence of previous psy-

chiatric disorders as a risk factor for the development of PTSS

Fig. 1. PRISMA flowchart of studies selection process.

C. Carmassi, et al. Psychiatry Research 292 (2020) 113312

3

T
ab

le
1

M
ai
n
ch

ar
ac
te
ri
st
ic
s
of

in
cl
u
d
ed

st
u
d
ie
s.

St
u
d
y

O
u
tb
re
ak

T
yp

e
Sa

m
p
le

P
T
SS

/P
T
SD

m
ea
su
re
s

M
ai
n
ge

n
er
al

fi
n
d
in
gs

M
ai
n
ri
sk

an
d
re
si
li
en

ce
fa
ct
or
s

B
ai

et
al
.
(2
0
0
4
)

SA
R
S

C
ro
ss
-s
ec
ti
on

al
st
u
d
y

5
5
7
h
os
p
it
al

st
aff

m
em

be
rs

(H
C
W
s
n
=

4
0
2
;
ad

m
in
is
tr
at
iv
e

p
er
so
n
n
el

n
=

1
5
5
)

SA
R
S-
re
la
te
d
st
re
ss

re
ac
ti
on

s
qu

es
ti
on

n
ai
re

5
%

ac
u
te

st
re
ss

d
is
or
d
er
;

2
0
%

st
ig
m
at
iz
ed

;
an

d
9
%

re
lu
ct
an

ce
to

w
or
k
or

co
n
si
d
er
ed

re
si
gn

at
io
n

R
is
k
fa
ct
or
:
qu

ar
an

ti
n
e

C
h
an

an
d
H
u
ak

(2
0
0
4
)

SA
R
S

C
ro
ss
-s
ec
ti
on

al
st
u
d
y

6
6
1
H
C
W
s
(d
oc

to
rs

an
d
n
u
rs
es
)

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e

2
0
%

IE
S
sc
or
e
>

3
0
;

2
7
%

p
sy
ch

ia
tr
ic

sy
m
p
to
m
s
(3
5
%

of
d
oc

to
rs

an
d
2
5
%

of
n
u
rs
es
)

R
es
il
ie
n
ce

fa
ct
or
s:

Su
p
p
or
t
fr
om

fa
m
il
y/

su
p
er
vi
so
rs
/c
ol
le
ag

u
es
;
w
or
k
or
ga

n
iz
at
io
n

(c
le
ar

d
ir
ec
ti
ve

s/
p
re
ca
u
ti
on

ar
y
m
ea
su
re
s

fr
om

m
an

ag
em

en
t)

C
h
on

g
et

al
.
(2
0
0
4
)

SA
R
S

n
at
u
ra
li
st
ic
,

ob
se
rv
at
io
n
al

st
u
d
y

1
2
5
7
h
os
p
it
al

st
aff

m
em

be
rs

(n
u
rs
es

n
=

6
7
6
;
d
oc

to
rs

n
=

1
3
9
;
h
ea
lt
h
ad

m
in
is
tr
at
iv
e

w
or
ke

rs
n
=

1
4
0
;
ot
h
er
s

n
=

3
0
2
)

Im
p
ac
t
of

E
ve

n
t
Sc
al
e

IE
S
m
ea
n
sc
or
e=

3
4
.8
;

7
5
.3
%

p
sy
ch

ia
tr
ic

sy
m
p
to
m
s
(a
n
xi
et
y
an

d
w
or
ry
in
g,

d
ep

re
ss
io
n
an

d
in
te
rp
er
so
n
al

d
iffi

cu
lt
ie
s,

so
m
at
ic

p
ro
bl
em

s)
in

th
e
in
it
ia
l
p
h
as
e
of

th
e
ou

tb
re
ak

R
is
k
fa
ct
or
s:

m
al
e;

te
ch

n
ic
ia
n
s;


2
ye

ar
s

w
or
k
ex
p
er
ie
n
ce
;
le
ve

l
of

ex
p
os
u
re

M
au

n
d
er

et
al
.
(2
0
0
4
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

1
5
5
7
H
C
W
s

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e

H
ig
h
er

Im
p
ac
t
of

E
ve

n
t
Sc
al
e
sc
or
es

ar
e
fo
u
n
d
in

n
u
rs
es

an
d
H
C
W
s
h
av

in
g
co

n
ta
ct

w
it
h
SA

R
S
p
at
ie
n
ts
.

R
is
k
fa
ct
or
s:

le
ve

l
of

ex
p
os
u
re
;
n
u
rs
es
;

p
er
ce
iv
ed

th
re
at

fo
r
th
ei
r
h
ea
lt
h
;
so
ci
al

is
ol
at
io
n

Si
m

et
al
.
(2
0
0
4
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

2
7
7
H
C
W
s

(d
oc

to
rs

n
=

9
1
;n

u
rs
es

n
=

1
8
6
)

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e

9
.4
%

P
T
SS

;
2
0
.6
%

p
sy
ch

ia
tr
ic

m
or
bi
d
it
y

R
is
k
fa
ct
or
s:

yo
u
n
ge

r
ag

e,
be

in
g
m
ar
ri
ed

,
p
sy
ch

ia
tr
ic

m
or
bi
d
it
y,

le
ss

ve
n
ti
n
g,

le
ss

h
u
m
or
,
an

d
le
ss

ac
ce
p
ta
n
ce
.

T
h
am

et
al
.
(2
0
0
4
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

E
m
er
ge

n
cy

H
C
W
s

(d
oc

to
rs

n
=

3
8
;

n
u
rs
es

n
=

5
8
)

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e

IE
S
sc
or
e

2
6
in

1
3
.2
%

d
oc

to
rs

an
d
2
0
.7
%

n
u
rs
es
;

G
en

er
al

H
ea
lt
h
Q
u
es
ti
on

n
ai
re
-2
8

5
in

1
5
.8
%

d
oc

to
rs

an
d
2
0
.7
%

n
u
rs
es

R
is
k
fa
ct
or
s:

n
u
rs
es

H
o
et

al
.
(2
0
0
5
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

8
2
H
C
W
s
n
ot

in
fe
ct
ed

an
d

9
7
H
C
W
s
w
h
o
re
co

ve
re
d
fr
om

SA
R
S

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e

(C
h
in
es
e
ve

rs
io
n
)

H
C
W
s
re
co

ve
re
d
re
p
or
te
d
h
ig
h
P
T
SS

in
tr
u
si
on

sy
m
p
to
m
s

an
d
m
or
e
co

n
ce
rn
s
ab

ou
t
ot
h
er

h
ea
lt
h
p
ro
bl
em

s
an

d
d
is
cr
im

in
at
io
n
.

H
C
W
s
n
ot

in
fe
ct
ed

h
ad

st
ro
n
ge

r
fe
ar

re
la
te
d
to

in
fe
ct
io
n

th
an

H
C
W
s
re
co

ve
re
d
;
eq

u
al

co
n
ce
rn

ab
ou

t
in
fe
ct
in
g

ot
h
er
s
(e
sp
ec
ia
ll
y
fa
m
il
y
m
em

be
rs
)
th
an

be
in
g
se
lf

in
fe
ct
ed

em
er
ge

d

R
is
k
fa
ct
or
s:

be
in
g
H
C
W
s
su
rv
iv
or
s

P
h
u
a
et

al
.
(2
0
0
5
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

9
9
H
C
V
s

(d
oc

to
rs

n
=

4
1
;
n
u
rs
e
n
=

5
8
)

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e

1
7
.7
%

IE
S
>

2
6
;

R
is
k
Fa

ct
or
:
n
u
rs
es

R
es
il
ie
n
ce

fa
ct
or
s:

p
os
it
iv
e
co

p
in
g
st
yl
es

(h
u
m
or

an
d
p
la
n
n
in
g)

K
w
ek

et
al
.
(2
0
0
6
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

6
3
H
C
W
s
SA

R
S
su
rv
iv
or
s

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e

4
1
%

sc
or
ed

in
d
ic
at
iv
e
of

P
T
SD

;
3
0
%

li
ke

ly
an

xi
et
y
an

d
d
ep

re
ss
io
n
.

R
is
k
fa
ct
or
:
be

in
g
H
C
W

su
rv
iv
or
s

M
au

n
d
er

et
al
.
(2
0
0
6
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

7
6
9
H
C
W
s

(S
A
R
S
an

d
n
o-
SA

R
S
u
n
it
s)

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e

SA
R
S
u
n
it
H
C
W
s
re
p
or
te
d
h
ig
h
er

P
T
SS

,
bu

rn
ou

t,
an

d
p
sy
ch

ol
og

ic
al

d
is
tr
es
s
ra
th
er

th
an

n
o-
SA

R
S
u
n
it
H
C
W
s.

SA
R
S
u
n
it
H
C
W
s
m
or
e
re
d
u
ce
d
p
at
ie
n
t

co
n
ta
ct

an
d
w
or
k
h
ou

rs
.

R
is
k
fa
ct
or
s:

m
al
ad

ap
ti
ve

co
p
in
g
st
ra
te
gi
es

(a
vo

id
an

ce
,
h
os
ti
le

co
n
fr
on

ta
ti
on

,
an

d
se
lf

bl
am

e)
.

R
es
il
ie
n
ce

fa
ct
or
s:

tr
ai
n
in
g,

Su
p
p
or
t
fr
om

fa
m
il
y/

su
p
er
vi
so
rs
/c
ol
le
ag

u
es
,
w
or
k

or
ga

n
iz
at
io
n

Le
e
et

al
.
(2
0
0
7
)

SA
R
S

co
h
or
t
st
u
d
y

SA
R
S
su
rv
iv
or
s
(n
on

–H
C
W
s

n
=

4
9
;
H
C
W
s
n
=

3
0
)

Im
p
ac
t
of

E
ve

n
t
Sc
al
e–
R
ev

is
ed

P
ar
ti
ci
p
an

ts
w
it
h
at

le
as
t
m
od

er
at
e
P
T
SS

re
p
or
te
d
3
2
.2
%

In
tr
u
si
on

,
2
0
.0
%

A
vo

id
an

ce
,
an

d
2
2
.2
%

H
yp

er
ar
ou

sa
l.

H
C
W

SA
R
S
su
rv
iv
or
s
w
er
e
m
or
e
d
is
tr
es
se
d
th
an

n
on

–H
C
W

on
e
ye

ar
af
te
r
th
e
ou

tb
re
ak

.

R
is
k
fa
ct
or
s:

be
in
g
H
C
W

su
rv
iv
or
s.

Li
n
et

al
.
(2
0
0
7
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

6
6
em

er
ge

n
cy

H
C
W
s
an

d
2
6
n
o-

em
er
ge

n
cy

H
C
W
s

D
av

id
so
n
T
ra
u
m
a
Sc
al
e-
C
h
in
es
e

ve
rs
io
n
(D

T
S-
C
)

E
m
er
ge

n
cy

H
C
W
s
re
p
or
te
d
>

D
T
S-
C
sc
or
es

th
an

n
o-

em
er
ge

n
cy

H
C
W
s;
2
1
,7
%

em
er
ge

n
cy

H
C
W
s
an

d
1
3
%

n
o-

em
er
ge

n
cy

H
C
W
s
re
p
or
te
d
D
T
S-
C
>
4
0
(s
u
sp
ec
te
d
P
T
SD

).

R
is
k
fa
ct
or
:
le
ve

l
of

ex
p
os
u
re

R
ey

n
ol
d
s
et

al
.
(2
0
0
7
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

1
0
5
7
qu

ar
an

ti
n
ed

su
bj
ec
ts

(H
C
W
s
n
=

2
6
9
)

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e

R
ev

is
ed

1
4
.6
%

IE
S-
R

2
0
;
qu

ar
an

ti
n
ed

H
C
W
s
ex
p
er
ie
n
ce
d

gr
ea
te
r
P
T
SS

th
an

qu
ar
an

ti
n
ed

n
o-
H
C
W
s

R
is
k
fa
ct
or
s:

qu
ar
an

ti
n
e

Su
et

al
.
(2
0
0
7
)

SA
R
S

p
ro
sp
ec
ti
ve

an
d

p
er
io
d
ic

fo
ll
ow

-u
p

st
u
d
y

1
0
2
H
C
W
s
(7
0
SA

R
S
an

d
3
2
n
o-

SA
R
S
H
C
W
s)

D
av

id
so
n
T
ra
u
m
a
Sc
al
e-
C
h
in
es
e

ve
rs
io
n
(D

T
S-
C
)

SA
R
S
u
n
it
H
C
W
s
re
p
or
te
d
h
ig
h
er

D
ep

re
ss
io
n
(3
8
.5
%

vs
.

3
.1
%
)
in
so
m
n
ia

(3
7
%

vs
.
9
.7
%
)
an

d
P
T
SS

(3
3
%

vs
.

1
8
.7
%
,
bu

t
n
ot

si
gn

ifi
ca
n
t)
.

R
is
k
fa
ct
or
s:

le
ve

l
of

ex
p
os
u
re

La
n
ce
e
et

al
.
(2
0
0
8
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

1
3
9
h
os
p
it
al

st
aff

(H
C
W
s

n
=

1
0
3
;
cl
er
ic
al

st
aff

n
=

1
3
;

O
th
er

n
=

2
1
)

St
ru
ct
u
re
d
C
li
n
ic
al

In
te
rv
ie
w

fo
r

D
SM

-I
V
;
C
li
n
ic
ia
n
-A
d
m
in
is
te
re
d

P
T
SD

Sc
al
e

3
0
%

li
fe
ti
m
e
p
re
va

le
n
ce

of
d
ep

re
ss
iv
e,

an
xi
et
y,

or
su
bs
ta
n
ce

u
se

d
ia
gn

os
is
.

5
%

n
ew

p
sy
ch

ia
tr
ic

d
is
or
d
er
s
af
te
r
ou

tb
re
ak

R
is
k
fa
ct
or
s:

p
re
vi
ou

s
p
sy
ch

ia
tr
ic

d
is
or
d
er
,

<
ye

ar
s
of

w
or
k
ex
p
er
ie
n
ce

(c
on

ti
nu

ed
on

ne
xt

pa
ge
)

C. Carmassi, et al. Psychiatry Research 292 (2020) 113312

4

T
ab

le
1
(c
on

ti
nu

ed
)

St
u
d
y

O
u
tb
re
ak

T
yp

e
Sa

m
p
le

P
T
SS

/P
T
SD

m
ea
su
re
s

M
ai
n
ge

n
er
al

fi
n
d
in
gs

M
ai
n
ri
sk

an
d
re
si
li
en

ce
fa
ct
or
s

R
es
il
ie
n
ce

fa
ct
or
s:

tr
ai
n
in
g
an

d
su
p
er
vi
so
r/

co
ll
ea
gu

es
su
p
p
or
t.

St
yr
a
et

al
.
(2
0
0
8
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

SA
R
S
u
n
it
s
H
C
W
s
(n

=
1
6
0
)
an

d
n
o-
SA

R
S
u
n
it
s
H
C
W
s
(n

=
8
8
)

Im
p
ac
t
of

E
ve

n
t
Sc
al
e—

R
ev

is
ed

H
C
W
s
ta
ki
n
g
ca
re

of
on

ly
on

e
SA

R
S
p
at
ie
n
t
h
ad

h
ig
h
er

P
T
SS

le
ve

ls
th
an

th
os
e
ta
ki
n
g
ca
re

of
n
on

e
or

m
or
e
th
an

tw
o
SA

R
S
p
at
ie
n
ts

R
is
k
fa
ct
or
:
le
ve

l
of

ex
p
os
u
re

W
u
et

al
.
(2
0
0
9
)

SA
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

5
4
9
h
os
p
it
al

st
aff

(2
1
%

d
oc

to
rs
,

3
8
%

n
u
rs
es
,
2
2
%

te
ch

n
ic
ia
n
s;

2
0
%

ad
m
in
is
tr
at
iv
e
an

d
ot
h
er
s)

Im
p
ac
t
of

E
ve

n
t
Sc
al
e—

R
ev

is
ed

A
bo

u
t
1
0
%

IE
S-
R

2
0
.

R
is
k
fa
ct
or
s:
le
ve

lo
f
ex
p
os
u
re
;y

ou
n
ge

r
ag

e;
qu

ar
an

ti
n
e/
is
ol
at
io
n
(q
u
ar
an

ti
n
e,

h
av

in
g

fr
ie
n
d
s
or

cl
os
e
re
la
ti
ve

s
in
fe
ct
ed

).
R
es
il
ie
n
ce

fa
ct
or
:
co

p
in
g
st
ra
te
gi
es

(a
lt
ru
is
ti
c
ac
ce
p
ta
n
ce

of
w
or
k-
re
la
te
d
ri
sk
s)

M
ak

et
al
.
(2
0
1
0
)

SA
R
S

re
tr
os
p
ec
ti
ve

co
h
or
t

st
u
d
y

9
0
SA

R
S
su
rv
iv
or
s
(3
0
%

H
C
W
s)

St
ru
ct
u
re
d
C
li
n
ic
al

In
te
rv
ie
w

fo
r

th
e
D
SM

-I
V
;

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e–
R
ev

is
ed

4
7
.8
%

P
T
SD

in
th
e
af
te
rm

at
h
of

SA
R
S.

2
5
.6
%

st
il
l
su
ff
er
s

P
T
SD

3
0
-m

on
th
s
p
os
t-
SA

R
S

R
is
k
fa
ct
or
s:

be
in
g
H
C
W
s
su
rv
iv
or
s

(b
u
t
la
rg
e
p
ro
p
or
ti
on

of
th
e
H
C
W
s
w
er
e

fe
m
al
e,

an
d
th
is

co
u
ld

aff
ec
t
re
su
lt
s)
.

W
in
g
an

d
Le

u
n
g
(2
0
1
2
)

SA
R
S

ca
se
-c
on

tr
ol

st
u
d
y

2
3
3
SA

R
S
su
rv
iv
or
s

C
h
in
es
e
bi
li
n
gu

al
ve

rs
io
n
of

th
e

Se
m
i-
St
ru
ct
u
re
d
C
li
n
ic
al

In
te
rv
ie
w

(S
C
ID

-I
)

Im
p
ac
t
of

E
ve

n
t
Sc
al
e-
re
vi
se
d

5
0
%

SA
R
S
su
rv
iv
or
s
a
li
fe
ti
m
e
p
sy
ch

ia
tr
ic

d
is
or
d
er

(d
ep

re
ss
io
n
,
P
T
SD

,
so
m
at
of
or
m

p
ai
n
d
is
or
d
er
,
p
an

ic
d
is
or
d
er
)

R
is
k
fa
ct
or
:
be

in
g
H
C
W
s
su
rv
iv
or
s

Le
e
et

al
.
(2
0
1
8
)

M
E
R
S

co
h
or
t
st
u
d
y

3
5
9
H
C
W
s

(M
E
R
S
an

d
n
o-
M
E
R
S
u
n
it
)

Im
p
ac
t
of

E
ve

n
ts

Sc
al
e–
R
ev

is
ed

5
1
%

H
C
W
s
re
p
or
te
d
IE
S>

2
5

(M
E
R
S
u
n
it
s
>

n
o-
M
E
R
S
u
n
it
s)

in
th
e
fi
rs
t
m
on

th
of

M
E
R
S
ou

tb
re
ak

.
A
ft
er

on
e
m
on

th
:
qu

ar
an

ti
n
ed

M
E
R
S

u
n
it
s
H
C
W
s
sh
ow

ed
h
ig
h
er

sl
ee
p
an

d
n
u
m
bn

es
s
sc
or
es
;

M
E
R
S
u
n
it
s
H
C
W
s
sh
ow

ed
h
ig
h
er

in
tr
u
si
on

sy
m
p
to
m
s

R
is
k
fa
ct
or
s:

le
ve

l
of

ex
p
os
u
re
,
qu

ar
an

ti
n
e

Ju
n
g
et

al
.
(2
0
2
0
)

M
E
R
S

cr
os
s-
se
ct
io
n
al

st
u
d
y

1
4
7
H
C
W
s
(n
u
rs
es

of
M
E
R
S
u
n
it
s)

Im
p
ac
t
of

E
ve

n
t
Sc
al
e–
R
ev

is
ed

K
or
ea
n
ve

rs
io
n

5
7
.1
%

P
T
SD

(2
5
.1
%

fu
ll
P
T
SD

an
d
3
2
.0
%

p
ar
ti
al

P
T
SD

).
P
T
SD

w
as

as
so
ci
at
ed

w
it
h
tu
rn
ov

er
in
te
n
ti
on

R
is
k
fa
ct
or
s:

le
ve

l
of

ex
p
os
u
re

(e
m
er
ge

n
cy

H
C
W
s
>

n
o-
em

eg
en

cy
H
C
W
s)
,
p
re
vi
ou

s
p
sy
ch

ia
tr
ic

d
is
or
d
er
s

R
es
il
ie
n
ce

fa
ct
or
:
su
p
er
vi
so
r
su
p
p
or
t

K
an

g
et

al
.
(2
0
2
0
)

C
O
V
ID

-1
9

cr
os
s-
se
ct
io
n
al

st
u
d
y

9
9
4
W
u
h
an

H
C
W
s
(d
oc

to
rs

an
d

n
u
rs
es
)

Im
p
ac
t
of

E
ve

n
t
Sc
al
e-
R
ev

is
ed

R
eg

ar
d
in
g
m
en

ta
l
h
ea
lt
h
p
ro
bl
em

(i
n
cl
u
d
in
g
P
T
SS

),
3
6
.9
%

h
ad

su
b-
th
re
sh
ol
d
d
is
tu
rb
an

ce
s,

3
4
.4
%

m
il
d

d
is
tu
rb
an

ce
s,

2
2
.4
%

m
od

er
at
e
d
is
tu
rb
an

ce
s,

an
d
6
.2
%

se
ve

re
d
is
tu
rb
an

ce
.

R
is
k
fa
ct
or
s:

le
ve

l
of

ex
p
os
u
re

(t
o
p
eo

p
le

ar
ou

n
d
th
em

w
h
o
w
er
e
in
fe
ct
ed

,
in
cl
u
d
in
g

fa
m
il
y/

co
ll
eg

u
es
/f
ri
en

d
s)
.

R
es
il
ie
n
ce

fa
ct
or
s:

co
p
in
g
st
ra
te
gi
es

(b
ei
n
g

m
ot
iv
at
ed

to
le
ar
n
th
e
n
ec
es
sa
ry

sk
il
ls

to
re
sp
on

d
to

d
iv
er
se

ch
al
le
n
ge

s)
La

i
et

al
.
(2
0
2
0
)

C
O
V
ID

-1
9

cr
os
s-
se
ct
io
n
al

st
u
d
y

1
2
5
7
H
C
W
s
(d
oc

to
rs

n
=

4
9
3
,

n
u
rs
es

n
=

7
6
4
)

Im
p
ac
t
of

E
ve

n
t
Sc
al
e–
R
ev

is
ed

7
1
.5
%

re
p
or
te
d
m
il
d
to

se
ve

re
P
T
SS

(3
6
.5
%

m
il
d
,
2
4
.5
%

m
od

er
at
e,

1
0
.5

se
ve

re
).

R
is
k
fa
ct
or
s:

le
ve

l
of

ex
p
os
u
re
,
n
u
rs
es
,

fe
m
al
e,

fe
w
er

ye
ar
s
of

w
or
k
ex
p
er
ie
n
ce
.

Li
et

al
.
(2
0
2
0
)

C
O
V
ID

-1
9

ca
se
-c
on

tr
ol

st
u
d
y

2
1
4
ge

n
er
al

p
u
bl
ic

an
d
5
2
6
H
C
W
s

(2
3
4
fr
on

t-
li
n
e
n
u
rs
es
,
2
9
2
n
on


fr
on

t-
li
n
e
n
u
rs
es
)

V
ic
ar
io
u
s
tr
au

m
at
iz
at
io
n

qu
es
ti
on

n
ai
re

(b
as
ed

on
se
ve

ra
l

qu
es
ti
on

n
ai
re
s,

in
cl
u
d
in
g
IE
S-
R
)

V
ic
ar
io
u
s
tr
au

m
at
iz
at
io
n
w
as

si
gn

ifi
ca
n
tl
y
lo
w
er

in
fr
on

t-
li
n
e
n
u
rs
es

th
an

n
on

-f
ro
n
t-
li
n
e
on

es
an

d
ge

n
er
al

p
u
bl
ic

(n
o
d
iff
er
en

ce
be

tw
ee
n
n
on

-f
ro
n
t-
li
n
e
n
u
rs
es

an
d
ge

n
er
al

p
u
bl
ic
)

R
is
k
fa
ct
or
s:

le
ve

l
of

ex
p
os
u
re
,
m
ar
it
al

st
at
u
s.

H
C
W
s:

h
ea
lt
h
ca
re

w
or
ke

rs
.

C. Carmassi, et al. Psychiatry Research 292 (2020) 113312

5

(Sim et al., 2004; Su et al., 2007; Lancee et al., 2008). Accordingly,
Su et al. (2007) on a sample of 70 nurses from two SARS units and 32
nurses from two non-SARS units found highlighted a previous history of
mood disorders as a major risk factor for PTSS. One study on MERS
outbreak confirmed this finding (Jung et al., 2020).

3.4. PTSD and PTSS resilience factors of in HCWs facing the three
coronavirus outbreaks

3.4.1. Family and social support
Two studies on the SARS outbreak highlighted the support of family

and friends as having a major role in protecting from PTSS development
(Chan and Huak, 2004; Su et al., 2007). In particular, Su et al. (2007)
investigating 102 nurses found that strong social and family support
protected against acute stress, with a positive impact on their global
functioning as a function of time.

3.4.2. Supervisors and colleagues support
Three researches concerning the SARS outbreak (Chan and

Huak, 2004; Maunder et al., 2006; Lancee et al., 2008) and one on the
MERS (Jung et al., 2020), reported a protective role of the support from
supervisors/colleagues. Particularly, Lancee et al. (2008), in 139 HCWs
in Canada, showed feeling well supported while working as a resilience
factor also in the long-term. Jung et al. (2020) noticed that manage-
ment strategies based on supervisors’ support proved helpful in order to
reduce PTSS in 147 nurses in three isolation hospitals in South Korea
during the MERS outbreak.

3.4.3. Training
The perception of being adequately trained was identified as a po-

tentially protective factor in two studies on the SARS (Maunder et al.,
2006; Lancee et al., 2008)., Comparing 769 Canadian HCWs displaced
in 9 hospitals that treated SARS patients and 4 hospitals that did not,
from 13 to 26 months after the outbreak, Maunder et al. (2006) sug-
gested the importance of supportive interventions in preventing PTSD
and PTSS with particular impact on maladaptive coping styles.

3.4.4. Work organization
The same authors reported that working in structured units and the

perceived safety of the working environment are further factors which
seem to enhance the resilience of HCWs, in line with findings of another
study by Su et al., 2007). Moreover, it has also been observed that a
clear communication of directives and precautionary measures to be
adopted was related to a better outcome with regard to PTSS (Chan and
Huak, 2004).

3.4.5. Coping strategies
In five studies on the SARS outbreak (Chan and Huak 2004;

Sim et al., 2004; Phua et al., 2005; Su et al., 2007; Wu et al., 2009),
positive coping strategies were reported to be a protective factor against
the development of PTSD psychopathology. Particularly, in a study
carried out in Singapore on 41 physicians and 58 nurses,
Phua et al. (2005) reported an association between the use of humor
and planning as coping strategies, and lower rates of PTSD. Other
protective coping styles included: the altruistic acceptance of work-re-
lated risks (Wu et al., 2009), the ability to talk to someone about their
experiences, and the presence of religious beliefs (Chan and Huak
2004). Accordingly, Maunder et al. (2006) found that maladaptive
coping strategies, such as avoidance, hostile confrontation and self-
blame, resulted in worse outcomes in terms of PTSS and
Sim et al. (2004) reported that less venting, humor and acceptance were
associated to higher levels of PTSS. Consistently, positive coping stra-
tegies, such as motivation to learning different skills, have been in-
dicated as resilience factors also in HMWs dealing with the current
COVID-19 pandemic (Kang et al., 2020).

3.5. HCWs survivors to coronavirus outbreaks

Five studies focusing on HCWs who survived the SARS infection
highlighted this population as particularly “at risk” for PTSD.
Kwek et al. (2006) in a sample of SARS survivors at 3 months post-
discharge found that HCWs were more affected by PTSS than non-
HCWs. Lee et al. (2007) examined a sample of 96 Hong Kong SARS
survivors divided into sub-samples of HCWs and non-HCWs, found that
while PTSS levels were similar in the two sub-samples at the peak of the
outbreak, HCWs compared to non-HCWs, reported significantly higher
PTSS one year after discharge, suggesting a lack of recovery as a
function of time, among HCW SARS survivors. In line with this, a later
study among 233 Chinese SARS survivors also reported a higher risk of
PTSD among HCW compared to non-HCW (Wing and Leung, 2012).
Furthermore, a study conducted on a sample of 90 Hong Kong SARS
survivors at 30 months after the outbreak (Mak et al., 2010) showed
that being a HCW was significantly associated with PTSD development,
despite the authors hypothesizing that this finding could be gender-
biased because the majority of the sample was made up of female
HCWs. Finally, Ho et al. (2005) in 97 HCWs in Hong Kong found a
positive correlation between the presence of pronounced SARS-related
fears and PTSS burden, particularly intrusion symptoms; in addition
HCWs who had recovered from SARS appeared to be more concerned
about death, discrimination and quarantine than those who had not
been infected.

4. Discussion

To the best of our knowledge we conducted the first review ad-
dressing PTSD and PTSS risk and resilience factors in HCWs who were
involved in the three major recent Coronavirus outbreaks, namely the
SARS, the MERS and the current COVID-19, which have affected the
worldwide population in the last two decades. Converging data suggest
a high risk for PTSD development among emergency HCWs, with stu-
dies consistently outlining several risk factors that are enhanced in the
case of these highly lethal outbreaks, such as: the frequent unpredict-
ability of daily caseloads, having to frequently manage patients and
their families’ expectations in unexpected critical cases/situations
(Mealer et al., 2009; Czaja et al., 2012; Iranmanesh et al., 2013;
Fjeldheim et al., 2014). In the context of an outbreak emergency such as
the COVID-19 crisis, difficulties are further heightened by the rapidly
increasing flow of critical patients requiring increased medical atten-
tion, the decision-making burden and high daily fatality rates, and the
constant updates of hospital procedures following advances in knowl-
edge about the disease, that creates another burden for HCWs who need
to keep up to date. Further, patients medical management requires tight
physical isolation, to protect patients and HCWs because of the ex-
tremely high risk of contamination (Petrie et al., 2018; Berger et al.,
2012; Brooks et al., 2019). Occupational role, marital status, age and
gender, quarantine, stigma, previous psychiatric disorders, isolation
and being survivors of the same outbreak also emerged as robust risk
factors for PTSS. In parallel, the literature highlighted a number of
resilience factors, such as support, training, prompt work organization
and good coping strategies.

The majority of studies included in our review focused on the 2003
SARS outbreak; fewer data were available on the MERS, and the studies
on COVID-19 are only emerging at the time of writing. All these studies
reported a high risk for adverse psychological reactions, particularly
PTSS and PTSD among HCWs, suggesting the proximity to “ground zero”
as a primary risk factor (Kwek et al., 2006; Lee et al., 2018). HCWs’ fear
of contagion and infection of their family, friends and colleagues,
feelings of uncertainty, stigmatization and rejection in their neighbor-
hood because of their hospital work were also reported. Studies also
reported the reluctance to work and/or considering quitting their job,
as well as high levels of stress, anxiety and depression symptoms, which
could have long-term psychological implications (Maunder et al., 2003;

C. Carmassi, et al. Psychiatry Research 292 (2020) 113312

6

Bai et al., 2004; Lee et al., 2007; Wu et al., 2009). The self-perceived
high risk for contagion might be the most important aspect related to
the front-line activities, with for example Su et al. (2007), failing to find
any significant difference between HCWs in SARS vs. non-SARS units in
PTSD prevalence rate. This suggests that not only HCWs working within
the SARS units, but also those working outside them and facing un-
certainty because of the displacement, might develop PTSS during the
outbreak. In this regard, in the ongoing COVID-19 pandemic, the lack of
personal protection devices represents a critical issue.

Interestingly, however, some authors found first-line exposure to
have a protective effect. Styra et al. (2008) reported that HCWs working
in SARS high risk units, as expected, experienced greater distress than
HCWs displaced in other departments such as the psychiatric one, but
contrary to expectations HCWs caring for many SARS patients while
working in high-risk units emerged as being less distressed. This finding
suggests that experience in treating SARS patients may be a mediating
factor that could be amenable to intervention in future outbreaks. This
is in line with more recent findings from a COVID-19 study, according
to which PTSS severity of non-front-line nurses was greater than that of
front-line nurses, who showed stronger psychological endurance. The
authors argue that this finding may be explained considering that front-
line nurses were voluntarily selected and provided with sufficient
psychological preparation. Moreover, the selected front-line nurses
were mainly middle-level backbone staff with working experience and
psychological capacity (Li et al., 2020).

Hence, there is evidence that perceived adequacy of training re-
presents a protective factor against adverse outcomes of traumatic ex-
posure (Maunder et al., 2006; Lancee et al., 2008). Similarly, other
factors concerning positive working organization, such as working in
structured units, a sense of protection of environment (Maunder et al.,
2006; Su et al., 2007) and clear communication of directives and of
precautionary measures (Chan and Huak, 2004), have proven to be
protective factors against the development of PTSS in HCWs. In parti-
cular, Chan and Huak (2004) explored the important role in preventing
PTSS of clear and prompt communication of directives and information
about the disease, of providing precautionary measures, such as Per-
sonal Protective Equipment (PPE), and of the support of a supervisor/
head of department, colleagues and family. The support from family
and friends as well as that from supervisors and colleagues has been
shown to represent an important resilience factor against the develop-
ment of PTSS, as widely demonstrated in the literature (Chan and
Huak, 2004; Maunder et al., 2006; Su et al., 2007; Lancee et al., 2008).
Nevertheless, this matter deserves further consideration since in this
peculiar clinical setting the implications of the contagion risk often lead
to self-isolation, with subsequent decreased social support.

Some important individual risk and resilience factors for PTSS have
also been reported among HCWs facing a coronavirus outbreak. First,
female gender. Despite the fact that the majority of the studies corro-
borate the preventive role of professional training as to PTSD onset up
to the point of flattening of the gender gap which is commonly observed
in PTSD reports, most of the studies on HCWs dealing with Coronavirus
outbreaks tend to show a higher incidence of PTSD among women.
Females, in fact, were shown to be most affected by PTSS in three SARS
studies (Lee et al., 2007; Reynolds et al., 2007; Lai et al., 2020), as well
as younger HCWs or HCWs with fewer years of work experience
(Reynolds et al., 2007; Lancee et al., 2008). Moreover, nurses proved to
be more affected by PTSS than other HCWs (Tham et al., 2004;
Maunder et al., 2004). Although this has been explained as related to
closer contact with infected patients, we may also argue that often the
nurse staff are mostly women. Further studies in this regard are thus
warranted. Outbreaks threatening family members’ well-being or af-
fecting children’s care, in fact, may constitute a burden for women
(Carmassi et al., 2019). It is worthy of note that all these factors could
be influenced by coping styles adopted by the HCWs to address the
psychic burden of the outbreak. Some studies focused on positive
coping styles that were associated to a better outcome (Phua et al.,

2005; Wu et al., 2009). Among these, Phua et al. (2005) found that
physicians chose humor as a coping strategy more frequently than
nurses, and this resulted in lower post-traumatic stress morbidity. Other
authors stressed the effect of maladaptive coping styles in predicting
PTSS, such as avoidance, hostile confrontation and self-blame
(Maunder et al., 2006).

As previously highlighted, the sense of isolation was found to be an
important factor related to PTSS. Consequently, HCWs who had been
quarantined were shown to be at higher risk (Bai et al., 2004) as well as
HCW survivors from the infection. These latter constitute a special
population in which the impact of infectious disease, along with related
fears for one’s health and for the contagion of loved ones and the sense
of isolation and the rejection due to the stigma, lead to a greater PTSS
burden (Wing and Leung, 2012).

More recently, scientists, clinicians and the general public, in fact,
have been increasingly referring to the current COVID-19 emergency
and its subsequent impact on health care systems, as the “9/11 of health
care systems”. First studies reported high levels of psychopathological
burden in HCWs dealing with the COVID-19 pandemic in China, in-
cluding depression, anxiety, insomnia and PTSS (Huang et al., 2020;
Kang et al., 2020; Lai et al., 2020). In particular, anxiety and PTSS
symptoms resulted higher in females, nurses and in HCWs with fewer
years of work experience (Lai et al., 2020; Huang et al., 2020). HCWs
are called to confront this new scenario under widespread media cov-
erage and in a context of a persisting imbalance between needs and
resources, increasing the decisional burden and the feelings of hope-
lessness; they are also forced to deal with challenging expectations of
the patients and their relatives in a framework characterized by unusual
communicative constraints. Moreover, the fear of contagion is ampli-
fied by the lack of personal protective equipment (PPE) and the high
number of infected or deceased colleagues, and is associated to the
concern of representing a threat to family members: this often leads to
self-isolation. As a consequence, loneliness, along with the risk of a
growing trend towards social stigmatization of HCWs as potential car-
riers of infection (WHO, 2020) results in deprivation of social support,
which is listed among the main factors of resilience.

Despite the slight decrease in the COVID-19 contagion rate, the
impact on HCWs mental health may produce enduring effects. Finally,
some evidence revealed a significant time-effect on reducing PTSD
symptom ratings, as observed in a SARS study by Su et al. (2007), re-
porting a 50% decrease after one month, no-one meeting the criteria for
PTSD. Conversely, a MERS study by Lee et al. (2018) reported that
HCWs performing one month before MERS-related tasks were at higher
risk for symptoms of PTSD even after time had passed, and the risk was
increased in sleep and numbness-related symptoms, in particular if
home quarantine was implemented.

For all these reasons, providing a timely response to psychological
pressure on HCWs in order to prevent negative mental health outcomes
requires the development of specific intervention strategies
(Carmassi et al., 2020c). Such strategies cannot but be based on a
careful survey of both risk and resilience factors that may be playing a
role in this special working population and should take into account
what the studies conducted in the aftermath of the previous outbreaks
reported.

When discussing our results some limitations should be considered.
First, the lack of a quality assessment of the studies. Second, we con-
sulted only one database for our search (PubMed). Third, most of the
included articles (N = 16) adopted the Impact of Event Scale scores,
which is a well-known rating scale that provides a subjective measure
of perceived stress (Horowitz et al., 1979; Marziali and Pilkonis, 1986;
Weiss et al., 1984), to detect PTSD or PTSS. Fourth, surveys give us a
limited glimpse into a complex psychological dynamic that happens
with healthcare providers in isolation wards, because they rely on vo-
luntary responses by the subjects, who may choose not to revisit a
traumatic experience by participating in the survey, thus leading to
under-reporting the incidence of traumatic sequelae (Li et al., 2020).

C. Carmassi, et al. Psychiatry Research 292 (2020) 113312

7

This is in line with Chen et al. (2020) who reported how the im-
plementation of psychological intervention services in the COVID-19
pandemic proved to be problematic, because medical staff were re-
luctant to participate in the group or individual psychology interven-
tions provided to them. Fifth, some studies reported that while quar-
antined HCWs consistently showed more frequent adverse
psychological impacts than non-HCWs, their experience was probably
influenced by their job-related experiences with SARS and not unique to
their HCW status (Reynolds et al., 2007). Finally, no information was
available on HCW family members, particularly on the possible impact
of the presence of children as a possible PTSS risk factor
(Carmassi et al., 2019).

We have examined studies carried out in the context of the three
Coronavirus outbreaks in order to outline PTSD and PTSS risk and re-
silience factors impacting on HCWs and to consistently enhance the
effectiveness of intervention strategies. While the COVID-19 pandemic
is straining healthcare systems all over the world, awareness of the
impact of the emergency on the HCWs’ mental health is rising, con-
sistently with evidence of the high risk of them developing psycholo-
gical distress, such as PTSD and PTSS, under similar circumstances. To
date, despite some recommendations released by international organi-
zations (WHO, 2020; Inter-Agency Standing Committee (IASC) 2020;
IFRC, 2020) and a variety of action proposals, a systematic approach is
not yet in place. Efficacious treatments for PTSD and PTSS exist
(Lee and Bowles, 2020; Charney et al., 2018; Dell’Osso et al., 2015), and
healthcare systems should also focus on prepare to roll out these
treatments among HCWs should prevention strategies fail to prevent
the development of these conditions.

CRediT authorship contribution statement

Claudia Carmassi: Conceptualization, Methodology, Investigation,
Writing – original draft, Writing – review & editing, Supervision.
Claudia Foghi: Methodology, Investigation, Writing – original draft,
Writing – review & editing. Valerio Dell’Oste: Conceptualization,
Methodology, Investigation, Writing – original draft, Writing – review &
editing. Annalisa Cordone: Investigation, Writing – original draft.
Carlo Antonio Bertelloni: Investigation, Writing – original draft. Eric
Bui: Conceptualization, Methodology, Writing – original draft, Writing –
review & editing, Supervision. Liliana Dell’Osso: Conceptualization,
Methodology, Writing – original draft, Supervision.

Declaration of Competing Interest

No conflict of interest. No disclosures to declare of any relationship
with a commercial company that has a direct financial interest in
subject matter or materials discussed in article or with a company
making a competing product.

Financial support

This research did not receive any specific grant from funding
agencies in the public, commercial or not-for-profit sectors.

Ethical standards

Not applicable.

Acknowledgments

Dr. Julia Antonia Elizabeth Gray, native English speaker, revised the
entire article.

Supplementary materials

Supplementary material associated with this article can be found, in
the online version, at doi:10.1016/j.psychres.2020.113312.

References

Ager, A., Pasha, E., Yu, G., Duke, T., Eriksson, C., Cardozo, B.L., 2012. Stress, mental
health, and burnout in national humanitarian aid workers in Gulu, Northern Uganda.
J. Trauma Stress 25, 713–720. https://doi.org/10.1002/jts.21764.

American Psychiatric Association (APA), 2013. Diagnostic and statistical manual of
mental disorders. DSM-5. American Psychiatric Press, Washington DC.

Bai, Y., Lin, C.C., Lin, C.Y., Chen, J.Y., Chue, C.M., Chou, P., 2004. Survey of stress re-
actions among health care workers involved with the SARS outbreak. Psychiatr. Serv.
55 (9), 1055–1057. https://doi.org/10.1176/appi.ps.55.9.1055.

Bao, Y., Sun, Y., Meng, S., Shi, J., Lu, L., 2020. 2019-nCoV epidemic: address mental
health care to empower society. Lancet 395 (10224), e37–e38. https://doi.org/10.
1016/S0140-6736(20)30309-3.

Berger, W., Coutinho, E.S., Figueira, I., Marques-Portella, C., Luz, M.P., Neylan, T.C.,
Marmar, C.R., Mendlowicz, M.V., 2012. Rescuers at risk: a systematic review and
meta-regression analysis of the worldwide current prevalence and correlates of PTSD
in rescue workers. Soc. Psychiatry Psychiatr. Epidemiol. 47 (6), 1001–1011. https://
doi.org/10.1007/s00127-011-0408-2.

Bonanno, G.A., Galea, S., Bucciarelli, A., Vlahov, D., 2007. What predicts psychological
resilience after disaster? The role of demographics, resources, and life stress. J.
Consult. Clin. Psychol. 75 (5), 671–682. https://doi.org/10.1037/0022-006X.75.5.
671.

Brewin, C.R., Andrews, B., Rose, S., Kirk, M., 1999. Acute stress disorder and posttrau-
matic stress disorder in victims of violent crime. Am. J. Psychiatry 156, 360–366.

Brooks, S.K., Rubin, G.J., Greenberg, N., 2019. Traumatic stress within disaster-exposed
occupations: overview of the literature and suggestions for the management of
traumatic stress in the workplace. Br. Med. Bull. 129 (1), 25–34. https://doi.org/10.
1093/bmb/ldy040.

Bryant, R.A., 2019. Post-traumatic stress disorder: a state-of-the-art review of evidence
and challenges. World Psychiatry 18 (3), 259–269. https://doi.org/10.1002/wps.
20656.

Carmassi, C., Barberi, F.M., Cordone, A., Maglio, A., Dell’Oste, V., Dell’Osso, L., 2020b.
Trauma, PTSD and post-traumatic stress spectrum: 15 years’ experience on a multi-
dimensional approach to trauma related psychopathology. Journal of
Psychopathology 26 (1), 4–11. https://doi.org/10.36148/2284-0249-376.

Carmassi, C., Bertelloni, C.A., Gesi, C., Conversano, C., Stratta, P., Massimetti, G., Rossi,
R., Dell’Osso, L., 2017. New DSM-5 PTSD guilt and shame symptoms among Italian
earthquake survivors: Impact on maladaptive behaviors. Psychiatry Research 251,
142–147. https://doi.org/10.1016/j.psychres.2016.11.026.

Carmassi, C., Cerveri, G., Bui, E., Gesi, C., Dell’Osso, L., 2020c. Defining Effective
Strategies to Prevent Post-Traumatic Stress in Healthcare Emergency Workers Facing
the COVID-19 Pandemic in Italy. CNS Spectrums 1–5. https://doi.org/10.1017/
S1092852920001637.

Carmassi, C., Corsi, M., Bertelloni, C.A., Pedrinelli, V., Massimetti, G., Peroni, D.G.,
Bonuccelli, A., Orsini, A., Dell’Osso, L., 2019. Post-traumatic stress and major de-
pressive disorder in parent caregivers of children with a chronic disorder. Psychiatry
Res. 279, 195–200. https://doi.org/10.1016/j.psychres.2019.02.062.

Carmassi, C., Gesi, C., Corsi, C., Cremone, I.M., Bertelloni, C.A., Massimetti, E., Olivieri,
M.C., Conversano, C., Santini, M., Dell’Osso, L., 2018. Exploring PTSD in emergency
operators of a major University Hospital in Italy: a preliminary report on the role of
gender, age, and education. Ann Gen Psychiatry 17, 17. https://doi.org/10.1186/
s12991-018-0184-4.

Carmassi, C., Gesi, C., Simoncini, M., Favilla, L., Massimetti, G., Olivieri, M.C.,
Conversano, C., Santini, M., Dell’Osso, L., 2016. DSM-5 PTSD and posttraumatic stress
spectrum in Italian emergency personnel: correlations with work and social adjust-
ment. Neuropsychiatr. Dis. Treat. 12, 375–381. https://doi.org/10.2147/NDT.
S97171.

Carmassi, C., Rossi, A., Pedrinelli, V., Cremone, I.M., Dell’Oste, V., Stratta, P., Bertelloni,
C.A., Dell’Osso, L., 2020a. PTSD in the aftermath of a natural disaster: what we
learned from the Pisa-L’Aquila Collaboration Project. J. Psychopathol. 26 (1),
99–106. https://doi.org/10.36148/2284-0249-377.

Chan, A.O., Huak, C.Y., 2004. Psychological impact of the 2003 severe acute respiratory
syndrome outbreak on health care workers in a medium size regional general hospital
in Singapore. Occup. Med. 54 (3), 190–196.

Charney, M.E., Hellberg, S.N., Bui, E., Simon, N.M., 2018. Evidenced-based treatment of
posttraumatic stress disorder: an updated review of validated psychotherapeutic and
pharmacological approaches. Harv. Rev. Psychiatry 26 (3), 99–115. https://doi.org/
10.1097/HRP.0000000000000186.

Chen, Q., Liang, M., Li, Y., Guo, J., Fei, D., Wang, L., He, L., Sheng, C., Cai, Y., Li, X.,
Wang, J., Zhang, Z., 2020. Mental health care for medical staff in China during the
COVID-19 outbreak. The Lancet Psychiatry 7 (4), e15–e16. https://doi.org/10.1016/
S2215-0366(20)30078-X.

Chong, M.Y., Wang, W.C., Hsieh, W.C., Lee, C.Y., Chiu, N.M., Yeh, W.C., Huang, O.L.,
Wen, J.K., Chen, C.L., 2004. Psychological impact of severe acute respiratory syn-
drome on health workers in a tertiary hospital. Br. J. Psychiatry 185, 127–133.
https://doi.org/10.1192/bjp.185.2.127.

Cieslak, R., Shoji, K., Douglas, A., Melville, E., Luszezynska, A., Benight, C.C., 2014. A
meta-analysis of the relationship between job bournout and secondary traumatic
stress among workers with indirect exposure to trauma. Psychol. Serv. 11 (1), 75.

C. Carmassi, et al. Psychiatry Research 292 (2020) 113312

8

Cleary, M., Kornhaber, R., Thapa, D.K., West, S., Visentin, D., 2018. The effectiveness of
interventions to improve resilience among health professionals: a systematic review.
Nurse Educ. Today 71, 247–263. https://doi.org/10.1016/j.nedt.2018.10.002.

Clohessy, S., Ehlers, A., 1999. PTSD symptoms, response to intrusive memories and
coping in ambulance service workers. Br. J. Clin. Psychol. 38 (3), 251–265.

Colville, G., Smith, J., Brierley, J., Citron, K., Nguru, N.M., Shaunak, P.D., Tam, O.,
Perkins-Porras, L., 2017. Coping with staff burnout and work-related posttraumatic
stress in intensive care. Pediatric Crit. Care Med. 18, e267–e273. https://doi.org/10.
1097/PCC.0000000000001179.

Crabbe, J.M., Bowley, D.M., Boffard, K.D., Alexander, D.A., Klein, S., 2004. Are health
professionals getting caught crossfire? The personal implications of caring for trauma
victims. Emerg. Med. J. 21 (5), 568–572.

Craun, S., Bourke, M., 2014. The use of humor to cope with secondary traumatic stress. J.
Child Sex Abuse 23, 840–852.

Czaja, A., Moss, M., Mealer, M., 2012. Symptoms of post-traumatic stress disorder among
pediatric acute care nurses. J. Pediatr. Nurs. 27 (4), 357–365. https://doi.org/10.
1016/j.pedn.2011.04.024.

de Wit, E., van Doremalen, N., Falzarano, D., Munster, V.J., 2016. SARS and MERS: recent
insights into emerging coronaviruses. Nat. Rev. Microbiol. 14, 523–534.

Dell’Osso, B., Albert, U., Atti, A.R., Carmassi, C., Carrà, G., Cosci, F., Del Vecchio, V., Di
Nicola, M., Ferrari, S., Goracci, A., Iasevoli, F., Luciano, M., Martinotti, G., Nanni,
M.G., Nivoli, A., Pinna, F., Poloni, N., Pompili, M., Sampogna, G., Tarricone, I., …,
Fiorillo, A., 2015. Bridging the gap between education and appropriate use of ben-
zodiazepines in psychiatric clinical practice. Neuropsychiatr. Dis. Treat. 11,
1885–1909. https://doi.org/10.2147/NDT.S83130.

DeLucia, J.A., Bitter, C., Fitzgerald, J., Greenberg, M., Dalwari, P., Buchanan, P., 2019.
Prevalence of post-traumatic stress disorder in emergency physicians in the United
States. West J. Emerg. Med. 20 (5), 740–746. https://doi.org/10.5811/westjem.
2019.7.42671.

Epstein, R.M., Krasner, M.S., 2013. Physician resilience: what it means, why it matters,
and how to promote it. Acad. Med. 88 (3), 301–303. https://doi.org/10.1097/acm.
0b013e318280cff0.

Figley, C.R., 1995. Compassion fatigue: coping with secondary traumatic stress disorder
in those who treat the traumatized. New York: Brunner-Mazel.

Fjeldheim, C.B., Nöthling, J., Pretorius, K., Basson, M., Ganasen, K., Heneke, R., Cloete,
K.J., Seedat, S., 2014. Trauma exposure, posttraumatic stress disorder and the effect
of explanatory variables in paramedic trainees. BMC Emerg. Med. 14, 11. https://doi.
org/10.1186/1471-227X-14-11.

Garbern, S.C., Ebbeling, L.G., Bartels, S.A., 2016. A systematic review of health outcomes
among disaster and humanitarian responders. Prehosp. Disaster Med. 31 (6),
635–642.

Grevin, F., 1996. Posttraumatic stress disorder, ego defense mechanisms, and empathy
among urban paramedics. Psychol. Rep. 79, 483–495.

Haber, Y., Palgi, Y., Hamama-Raz, Y., Shrira, A., Ben-Ezra, M., 2013. Predictors of pro-
fessional quality of life among physicians in a conflict setting: the role of risk and
protective factors. Isr. J. Psychiatry Relat. Sci. 50, 174–181.

Hamid, A., Musa, S., 2017. The mediating effects of coping strategies on the relationship
between secondary traumatic stress and burnout in professional caregivers in the
UAE. J. Ment. Health 26, 28–35.

Hegg-Deloye, S., Brassard, P., Jauvin, N., Prairie, J., Larouche, D., Poirier, P., Tremblay,
A., Corbeil, P., 2013. Current state of knowledge of post-traumatic stress, sleeping
problems, obesity and cardiovascular disease in paramedics. Emerg. Med. J. 31 (3),
242–247.

Ho, S.M., Kwong-Lo, R.S., Mak, C.W., Wong, J.S., 2005. Fear of severe acute respiratory
syndrome (SARS) among health care workers. J. Consult. Clin. Psychol. 73 (2),
344–349. https://doi.org/10.1037/0022-006X.73.2.344.

Horowitz, M., Wilner, N., Alvarez, W., 1979. Impact of event scale: a measure of sub-
jective stress. Psychosom. Med. 41 (3), 209–218. https://doi.org/10.1097/
00006842-197905000-00004.

Inter-Agency Standing Committee (IASC), 2020. Briefing note on addressing mental
health and psychosocial aspects of COVID-19 Outbreak-Version 1.1. https://
interagencystandingcommittee.org/iasc-reference-group-mental-health-and-
psychosocial-support-emergency-settings/interim-briefing.

International Federation of Red Cross and Red Crescent Societies (IFRC), 2020. Mental
health and psychosocial support for staff, volunteers and communities in anout-
breakof novel Coronavirus. https://pscentre.org/wp-content/uploads/2020/02/
MHPSS-in-nCoV-2020_ENG-1.pdf.

Huang, J.Z., Han, M.F., Luo, T.D., Ren, A.K., Zhou, X.P., 2020. [Mental health survey of
medical staff in a tertiary infectious disease hospital for COVID-19]. Zhonghua Lao
Dong Wei Sheng Zhi Ye Bing Za Zhi 38 (3), 192–195. https://doi.org/10.3760/cma.j.
cn121094-20200219-00063.

Iranmanesh, S., Tirgari, B., Sheikh, H., 2013. Post-traumatic stress disorder among
paramedic and hospital emergency personnel in south-east. World J. Emerg. Med. 4
(1), 26–31. https://doi.org/10.5847/wjem.j.issn.1920-8642.2013.01.005.

Jung, H., Jung, S.Y., Lee, M.H., Kim, M.S., 2020. Assessing the presence of post-traumatic
stress and turnover intention among nurses post-Middle East respiratory syndrome
outbreak: the importance of supervisor support. Workplace Health Saf. 68 (7),
337–345. https://doi.org/10.1177/2165079919897693.

Kang, L., Ma, S., Chen, M., Yang, J., Wang, Y., Li, R., Yao, L., bai, H., Cai, Z., Xiang Yang,
B., Hu, S., Zhang, K., Wang, G., Ma, C., Liu, Z., 2020. Impact on mental health and
perceptions of psychological care among medical and nursing staff in Wuhan during
the 2019 novel coronavirus disease outbreak: a cross-sectional study. Brain Behav.
Immun. 87, 11–17. https://doi.org/10.1016/j.bbi.2020.03.028.

Karanikola, M., Giannakopoulou, M., Mpouzika, M., Kaite, C.P., Tsiaousis, G.Z.,
Papathanassoglou, E.D., 2015. Dysfunctional psychological responses among
Intensive Care Unit nurses: asystematic review of the literature. Rev. Esc. Enferm.

USP 49 (5), 847–857.
Kwek, S.K., Chew, W.M., Ong, K.C., Ng, A.W., Lee, L.S., Kaw, G., Leow, M.K., 2006.

Quality of life and psychological status in survivors of severe acute respiratory syn-
drome at 3 months postdischarge. J. Psychosom. Res. 60 (5), 513–519. https://doi.
org/10.1016/j.jpsychores.2005.08.020.

Lai, J., Ma, S., Wang, Y., Cai, Z., Hu, J., Wu, J., Du, H., Chen, T., Li, R., Tan, H., Kang, L.,
Yao, L., Huang, M., Wang, H., Wang, G., Liu, Z., Hu, S., 2020. Factors associated with
mental health outcomes among health care workers exposed to coronavirus disease
2019. JAMA Netw. Open 3 (3), e203976. https://doi.org/10.1001/
jamanetworkopen.2020.3976.

Lancee, W.J., Maunder, R.G., Goldbloom, D.S., 2008. Coauthors for the impact of SARS
study, 2008. Prevalence of psychiatric disorders among Toronto hospital workers one
to two years after the SARS outbreak. Psychiatr. Serv. 59 (1), 91–95. https://doi.org/
10.1176/ps.2008.59.1.91.

Lee, A.M., Wong, J.G., McAlonan, G.M., Cheung, V., Cheung, C., Sham, P.C., Chu, C.-M.,
Wong, P.-C., Tsang, K.W.T., Chua, S.E., 2007. Stress and psychological distress among
SARS survivors 1 year after the outbreak. Can. J. Psychiatry 52 (4), 233–240. https://
doi.org/10.1177/070674370705200405.

Lee, E., Bowles, K., 2020. Navigating treatment recommendations for PTSD: a rapid re-
view. Int. J. Ment. Health. 1–41. https://doi.org/10.1080/00207411.2020.1781407.

Lee, S.M., Kang, W.S., Cho, A.R., Kim, T., Park, J.K., 2018. Psychological impact of the
2015 MERS outbreak on hospital workers and quarantined hemodialysis patients.
Compr. Psychiatry 87, 123–127 10.1016/j.comppsych.2018.10.003 PMCID:
PMC7094631.

Leung, G.M., Hedley, A.J., Ho, L.M., Chau, P., Wong, I.O., Thach, T.Q., Ghani, A.C.,
Donnelly, C.:.A., Fraser, C., Riley, S., Ferguson, N.M., Anderson, R.M., Tsang, T.,
Leung, P.Y., Wong, V., Chan, J.C., Tsui, E., Lo, S.V., Lam, T.H., 2004. The epide-
miology of severe acute respiratory syndrome in the 2003 Hong Kong epidemic: an
analysis of all 1755 patients. Ann. Intern. Med. 141 (9), 662–673.

Li, Z., Ge, J., Yang, M., Feng, J., Qiao, M., Jiang, R., Bi, J., Zhan, G., Xu, X., Wang, L.,
Zhou, Q., Zhou, C., Pan, Y., Liu, S., Zhang, H., Yang, J., Zhu, B., Hu, Y., Hashimoto,
K., Jia, Y., Wang, H., Wang, R., Liu, C., Yang, C., 2020. Vicarious traumatization in
the general public, members, and non-members of medical teams aiding in COVID-19
control. Brain Behav. Immun. S 0889-1591 (20). https://doi.org/10.1016/j.bbi.2020.
03.007. 30309-3.

Lin, C.Y., Peng, Y.C., Wu, Y., Chang, J., Chan, C.H., Yang, D.Y., 2007. The psychological
effect of severe acute respiratory syndrome on emergency department staff. Emerg.
Med. J. 24 (1), 12–17. https://doi.org/10.1136/emj.2006.035089.

Lu, Y.C., Shu, B.C., Chang, Y.Y., Lung, F.W., 2006. The mental health of hospital workers
dealing with severe acute respiratory syndrome. Psychother. Psychosom. 75 (6),
370–375.

Machado, D.A., Figueiredo, N.M.A., Velasques, L.S., Bento, C.A.M., Machado, W.C.A.,
Vianna, L.A.M., 2018. Cognitive changes in nurses working in intensive care units.
Rev. Bras. Enferm. 71 (1), 73–79. https://doi.org/10.1590/0034-7167-2016-0513.

Mak, I.W., Chu, C.M., Pan, P.C., Yiu, M.G., Ho, S.C., Chan, V.L., 2010. Risk factors for
chronic post-traumatic stress disorder (PTSD) in SARS survivors. Gen. Hosp.
Psychiatry 32 (6), 590–598. https://doi.org/10.1016/j.genhosppsych.2010.07.007.

Martin, C.E., Vujanovic, A.A., Paulus, D.J., Bartlett, B., Gallagher, M.W., Tran, J.K., 2017.
Alcohol use and suicidality in firefighters: associations with depressive symptoms and
posttraumatic stress. Comp. Psych. 74, 44–52. https://doi.org/10.1016/j.comppsych.
2017.01.002.

Marziali, E.A., Pilkonis, P.A., 1986. The measurement of subjective response to stressful
life events. J. Human Stress. Spring. 12 (1), 5–12. https://doi.org/10.1080/
0097840X.1986.9936760.

Maunder, R.G., Hunter, J., Vincent, L., Bennett, J., Peladeau, N., Leszcz, M., Sadavoy, J.,
Verhaeghe, L.M., Steinberg, R., Mazzulli, T., 2003. The immediate psychological and
occupational impact of the 2003 SARS outbreak in a teaching hospital. CMAJ 168
(10), 1245‐51.

Maunder, R.G., Lancee, W.J., Balderson, K.E., Bennett, J.P., Borgundvaag, B., Evans, S.,
Fernandes, C.M.B., Goldbloom, D.S., Gupta, M., Hunter, J.J., McGillis Hall, L., Nagle,
L.M., Pain, C., Peczeniuk, S.S., Raymond, G., Read, N., Rourke, S.B., Steinberg, R.J.,
Stewart, T.E., VanDeVelde-Coke, S., Veldhorst, G.G., Wasylenki, D.A., 2006. Long-
term psychological and occupational effects of providing hospital healthcare during
SARS outbreak. Emerg. Infect. Dis. 12 (12), 1924–1932. https://doi.org/10.3201/
eid1212.060584.

Maunder, R.G., Rourke, S., Hunter, J.J., Goldbloom, D., Balderson, K., Petryshen, P.,
Steinberg, R., Wasylenki, D., Koh, D., Fones, C.S., 2004. Factors associated with the
psychological impact of severe acute respiratory syndrome on nurses and other
hospital workers in Toronto. Psychosom. Med. 66 (6), 938–942.

McAlonan, G.M., Lee, A.M., Cheung, V., Cheung, C., Tsang, K.W.T., Sham, P.C., Chua,
S.E., Wong, J.G.W.S., 2007. Immediate and sustained psychological impact of an
emerging infectious disease outbreak on health care workers. Can. J. Psychiatry 52
(4), 241–247. https://doi.org/10.1177/070674370705200406.

McGarry, S., Girdler, S., McDonald, A., Valentine, J., Lee, S.L., Blair, E., Wood, F., Elliott,
C., 2013. Paediatric health-care professionals: relationships between psychological
distress, resilience and coping skills. J. Paediatr. Child. Health. 49, 725–732. https://
doi.org/10.1111/jpc.12260.

Mealer, M., Burnham, E.L., Goode, C.J., Rothbaum, B., Moss, M., 2009. The prevalence
and impact of post traumatic stress disorder and burnout syndrome in nurses.
Depress. Anxiety 26 (12), 1118–1126. https://doi.org/10.1002/da.20631.

Moher, D., Liberati, A., Tetzla, J., Altman, D.G., 2009. The PRISMA Group preferred re-
porting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS.
Med. 6, e1000097.

Nishiura, H., 2020. The extent of transmission of novel coronavirus in Wuhan. China. J.
Clin. Med. 9, 330.

Ozer, E.J., Best, S.R, Lipsey, T.L., Weiss, D.S., 2003. Predictors of posttraumatic stress

C. Carmassi, et al. Psychiatry Research 292 (2020) 113312

9

disorder and symptoms in adults: a meta-analysis. Psychol. Bull. 129 (1), 52–73.
Peeri, N.C., Shrestha, N., Rahman, M.S., Zaki, R., Tan, Z., Bibi, S., Baghbanzadeh, M.,

Aghamohammadi, N., Zhang, W., Haque, U., 2020. The SARS, MERS and novel
coronavirus (COVID-19) epidemics, the newest and biggest global health threats:
what lessons have we learned. Int. J. Epidemiology. https://doi.org/10.1093/ije/
dyaa033. Int J Epidemiol. dyaa033.

Perlman, S.E., Friedman, S., Galea, S., Nair, H.P., Eros-Samyal, M., Stellman, S.D., Hon, J.,
Greene, C.M., 2011. Short-term and medium-term health effects of 9/11. Lancet 378
(9794), 925–934. https://doi.org/10.1016/S0140-6736(11)60967-7.

Petrie, K., Milligan-Saville, J., Gayed, A., Deady, M., Phelps, A., Dell, L., Forbes, D.,
Bryant, R.A., Calvo, R.A., Glozier, N., Harvey, S.B., 2018. Prevalence of PTSD and
common mental disorders amongst ambulance personnel: a systematic review and
meta-analysis. Soc. Psychiatry Psychiatr. Epidemiol. 53 (9), 897–909. https://doi.
org/10.1007/s00127-018-1539-5.

Phua, D.H., Tang, H.K., Tham, K.Y., 2005. Coping responses of emergency physicians and
nurses to the 2003 severe acute respiratory syndrome outbreak. Acad. Emerg. Med.
12 (4), 322–328.

Reynolds, D.L., Garay, J.R., Deamond, S.L., Moran, M.K., Gold, W., Styra, R., 2007.
Understanding, compliance and psychological impact of the SARS quarantine ex-
perience. Epidemiol. Infect. 136 (7), 997–1007.

Robertson, N., Perry, A., 2010. Institutionally based health care workers’ exposure to
traumatogenic events:systematic review of PTSD presentation. J. Trauma Stress 23
(3), 417–420.

Sim, K., Chong, P.N., Chan, Y.H., Soon, W.S., 2004. Severe acute respiratory syndrome-
related psychiatric and posttraumatic morbidities and coping responses in medical
staff within a primary health care setting in Singapore. J. Clin. Psychiatry 65 (8),
1120–1127. https://doi.org/10.4088/jcp.v65n0815.

Styra, R., Hawryluck, L., Robinson, S., Kasapinovic, S., Fones, C., Gold, W.L., 2008.
Impact on health care workers employed in high-risk areas during the Toronto SARS
outbreak. J. Psychosom. Res. 64 (2), 177–183. https://doi.org/10.1016/j.jpsychores.
2007.07.015.

Su, T.P., Lien, T.C., Yang, C.Y., Su, Y.L., Wang, J.H., Tsai, S.L., Yin, J.C., 2007. Prevalence
of psychiatric morbidity and psychological adaptation of the nurses in a structured
SARS caring unit during outbreak: a prospective and periodic assessment study in
Taiwan. J. Psychiatr. Res. 41 (1–2), 119–130. https://doi.org/10.1016/j.jpsychires.

2005.12.006.
Tham, K.Y., Tan, Y.H., Tang, H.K., 2004. Psychological morbidity among emergency

department doctors and nurses after the SARS outbreak. Hong Kong J. Emerg. Med.
12 (4), 215–223. https://doi.org/10.1177/102490790501200404.

Vance, M.C., Kovachy, B., Dong, M., Bui, E., 2018. Peritraumatic distress: a review and
synthesis of 15 years of research. J. Clin. Psychol. 74 (9), 1457–1484. https://doi.
org/10.1002/jclp.22612.

Wang, C., 2020. A novel coronavirus outbreak of global health concern. Lancet 395,
470–473.

Weiss, D.S., Horowitz, M.J., Wilner, N., 1984. The stress response rating scale: a clin-
ician’s measure for rating the response to serious life-events. Br. J. Clin. Psychol. 23
(Pt 3), 202–215.

Wing, Y.K., Leung, C.M., 2012. Mental health impact of severe acute respiratory syn-
drome: a prospective study. Hong Kong Med. J. 18 (Suppl 3), 24–27.

Winkel, A.F., Robinson, A., Jones, A.A., Squires, A.P., 2019. Physician resilience: a
grounded theory study of obstetrics and gynaecology residents. Med. Educ. 53,
184–194. https://doi.org/10.1111/medu.13737.

World Health Organization, 2004. Summary of probable SARS cases with onset of illness
from 1 November 2002 to 31 July 2003. http://www.who.int/csr/sars/country/
table2004_04_21/en/.

World Health Organization. 2020. Mental health and psychosocial considerations during
the COVID-19 outbreak, 18 March 2020. https://apps.who.int/iris/handle/10665/
331490.

Wrenn, G.L., Wingo, A.P., Moore, R., Pelletier, T., Gutman, A.R., Bradley, B., Ressler, K.J.,
2011. Dr. Glenda L. Wrenn, The effect of resilience on posttraumatic stress disorder in
trauma-exposed inner-city primary care patients. J. Natl. Med. Assoc. 103 (7),
560–566. https://doi.org/10.1016/s0027-9684(15)30381-3.

Wu, P., Fang, Y., Guan, Z., Fan, B., Kong, J., Yao, Z., Liu, X., Fuller, C.J., Susser, E., Lu, J.,
Hoven, C.W., 2009. The psychological impact of the SARS epidemic on hospital
employees in China: exposure, risk perception, and altruistic acceptance of risk. Can.
J. Psychiatry 54 (5), 302–311. https://doi.org/10.1177/070674370905400504.

Yehuda, R., Hoge, C., McFarlane, A., Vermetten, E., Lanius, R.A., Nievergelt, C.M.,
Hobfoll, S.E., Koenen, K.C., Neylan, T.C., Hyman, S.E., 2015. Post-traumatic stress
disorder. Nat. Rev. Dis. Primers 1, 150–157. https://doi.org/10.1038/nrdp.2015.57.

C. Carmassi, et al. Psychiatry Research 292 (2020) 113312

10

  • PTSD symptoms in healthcare workers facing the three coronavirus outbreaks: What can we expect after the COVID-19 pandemic
    • Introduction
    • Methods
      • Search strategy
      • Eligibility criteria
      • Study selection
    • Results
      • Process of study selection
      • Characteristics of included studies
      • PTSD and PTSS risk factors in HCWs facing the coronavirus outbreaks
        • Level of exposure
        • Occupational role
        • Age and gender
        • Marital status
        • Quarantine, isolation and stigma
        • Previous psychiatric disorders
      • PTSD and PTSS resilience factors of in HCWs facing the three coronavirus outbreaks
        • Family and social support
        • Supervisors and colleagues support
        • Training
        • Work organization
        • Coping strategies
      • HCWs survivors to coronavirus outbreaks
    • Discussion
    • CRediT authorship contribution statement
    • Declaration of Competing Interest
    • Financial support
    • mk:H1_28
    • Ethical standards
    • mk:H1_30
    • Acknowledgments
    • mk:H1_32
    • Supplementary materials
    • References

Contents lists available at ScienceDirect

Psychiatry Research

journal homepage: www.elsevier.com/locate/psychres

Factors associated with depression, anxiety, and PTSD symptomatology
during the COVID-19 pandemic: Clinical implications for U.S. young adult
mental health

Cindy H. Liu (PhD)a,c,d,⁎, Emily Zhang (MA)a,c, Ga Tin Fifi Wong (BA)a,c, Sunah Hyun (PhD)a,c,
Hyeouk “Chris” Hahm (PhD)b,c

a Department of Newborn Medicine, Brigham and Women’s Hospital, Boston, MA, USA
b Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA, USA
c School of Social Work, Boston University, Boston, MA, USA
d Harvard Medical School

A R T I C L E I N F O

Keywords:
Psychological stress, Loneliness
University health services
Social support
Ethnicity
COVID-19
Depression
Anxiety
PTSD

A B S T R A C T

This study sought to identify factors associated with depression, anxiety, and PTSD symptomatology in U.S.
young adults (18-30 years) during the COVID-19 pandemic. This cross-sectional online study assessed 898
participants from April 13, 2020 to May 19, 2020, approximately one month after the U.S. declared a state of
emergency due to COVID-19 and prior to the initial lifting of restrictions across 50 U.S. states. Respondents
reported high levels of depression (43.3%, PHQ-8 scores ≥ 10), high anxiety scores (45.4%, GAD-7 scores ≥
10), and high levels of PTSD symptoms (31.8%, PCL-C scores ≥ 45). High levels of loneliness, high levels of
COVID-19-specific worry, and low distress tolerance were significantly associated with clinical levels of de-
pression, anxiety, and PTSD symptoms. Resilience was associated with low levels of depression and anxiety
symptoms but not PTSD. Most respondents had high levels of social support; social support from family, but not
from partner or peers, was associated with low levels of depression and PTSD. Compared to Whites, Asian
Americans were less likely to report high levels across mental health symptoms, and Hispanic/Latinos were less
likely to report high levels of anxiety. These factors provide initial guidance regarding the clinical management
for COVID-19-related mental health problems.

1. Introduction

The COVID-19 pandemic that has upended the lives of individuals
worldwide escalated in the U.S. beginning in March of 2020. Although
research on acute and widescale stressors (e.g., natural disasters), de-
monstrates severe implications for mental health (Kessler et al., 2008),
there is no precedent for understanding the mental health effects due to
COVID-19, as prospective studies investigating the effects of a pan-
demic are virtually non-existent. In particular, the identification of risk
factors associated with depression, anxiety, and post-traumatic stress
disorder (PTSD) among U.S. young adults (18-30 years) during the
pandemic is urgently needed. Comprising more than one-third of the
current U.S. workforce, young adults (often referred to as “Millennials”
and “Generation Z”) will be a dominant workforce group for the next
decade, and our societal functioning depends on how they emerge from
the pandemic. Understanding their health and well-being now is crucial

as it sets the stage for later outcomes.
Certain risk and protective factors are likely to be implicated in

pandemic-related mental health. COVID-19-related worry (e.g., main-
taining employment, getting tested for coronavirus) may be linked to
mental health symptoms. The early weeks of the pandemic saw rapid
changes in daily routines, with students moving following university
closures and attending classes remotely, and for other young adults,
transitioning to remote work or experiencing loss of work. These dis-
ruptions may put an already vulnerable group at greater risk for mental
health challenges (Conrad, 2020). Furthermore, loneliness may be
particularly prevalent and devastating during the pandemic given di-
rectives for social distancing and isolation. Those under the age of 25
already show elevated levels of loneliness (Domagala-Krecioch and
Majerek, 2013), and the pandemic may exacerbate these feelings. De-
spite the critical role that social support plays in mitigating the risks to
mental health problems, directives on social distancing may impede on

https://doi.org/10.1016/j.psychres.2020.113172
Received 28 April 2020; Received in revised form 30 May 2020; Accepted 30 May 2020

⁎ Corresponding author.
E-mail address: [email protected] (C.H. Liu).

Psychiatry Research 290 (2020) 113172

Available online 01 June 2020
0165-1781/ © 2020 Elsevier B.V. All rights reserved.

T

one’s typical means for obtaining such support.
Individual resilience, which refers to one’s ability to cope with

stress, and distress tolerance, which describes one’s ability to manage
and tolerate emotional distress, may be salient characteristics that
protect against the mental health symptoms that follow major stressors.
Individual resilience is a significant protective factor for depression,
PTSD, and general health after natural disasters (Kukihara et al., 2014).
Findings have generally demonstrated distress tolerance to be asso-
ciated with lower symptoms of depression and PTSD following torna-
does (Cohen et al., 2016). However, the extent to which these factors
are associated with mental health symptoms during a pandemic is un-
known.

This study sought to identify potential factors that contribute to
mental health outcomes among young adults during the COVID-19
pandemic. The CARES 2020 Project (COVID-19 Adult Resilience
Experiences Study, www.cares2020.com) was launched to track the
health and well-being of young adults in the U.S. across multiple time
points in 2020 and 2021. This present analysis assessed depression,
anxiety, and PTSD symptomatology, and psychological experiences
including distress tolerance, resilience, social support, and loneliness.
We included depression and anxiety as these are common mental health
symptoms among young adults (Blazer et al., 1994; Chen et al., 2019;
Eisenberg et al., 2007; Liu et al., 2019; Mojtabai et al., 2016). We as-
sessed PTSD symptoms given documented high rates of trauma by
young adulthood (Costello et al., 2002; Reynolds et al., 2016; Vrana and
Lauterbach, 1994); a concern was that the pandemic would either
create and/or exacerbate symptoms related to prior trauma
(Breslau et al., 2008, 1999; Brunet et al., 2001). New items that as-
sessed COVID-19-specific concerns were also included. The objective of
this work is to identify salient psychosocial risks for mental health
symptoms and to prioritize intervention targets for addressing mental
health symptoms among young adults.

2. Methods

2.1. Study population

This present cross-sectional study assessed potential risk and pro-
tective factors for mental health outcomes based on preliminary CARES
2020 data obtained from Wave 1 data collection (N = 898) conducted
from April 13, 2020 to May 19, 2020, approximately one month after
the U.S. declared a state of emergency due to COVID-19 and prior to the
initial lifting of restrictions across 50 U.S. states. Eligible participants
were young adults aged 18 to 30 years currently living in the U.S. or
receiving education from a U.S. institution. Participants were recruited
online via email list serves, social media, and word of mouth (i.e., list
serves and Facebook groups for school organizations or clubs, alumni
groups, classes, churches). This took place initially through organiza-
tions from the New England area before additional list serves from
other regions of the U.S. (Midwest, South, and West) were targeted.
Respondents were asked to complete a 30-minute online Qualtrics
survey regarding COVID-19-related experiences, risk and resilience,
and physical and mental health outcomes. To ensure data quality,
human verification and attention checks were implemented throughout
the survey; the data were further inspected visually for response irre-
gularities indicative of bots. Participants were compensated via raffle in
which one out of every 10 participants received a $25 gift card. All
procedures were approved by the Institutional Review Board at Boston
University.

2.2. Measures

Binary scores were created after calculating the mean or sum of
each measure. Rather than relying on the sample characteristics to
categorize our data (e.g., mean, median, tertile or quartile split), the
determination of the cutoff score was based on standard cutoffs from

previous research; when a standard was not available, scale response
descriptors to determine the cutoffs.

2.2.1. Risk and protective factors
Psychological resilience was measured using the 10-item Connor-

Davidson Resilience Scale (CD-RISC-10, Connor and Davidson, 2003),
which assesses one’s ability to cope with adverse experiences. Partici-
pants indicated how they felt in the past month on a 5-point scale, with
0 indicating “not true at all” and 4 indicating “true nearly all the time.”
Sum scores were recoded dichotomously into “high resilience” and “low
resilience” with a cutoff score of 30 or greater. This cutoff score char-
acterizes responses that tended to be “often true” and “true nearly all
the time,” with those endorsing a score ≥30 considered to be at “very
high risk with mental disorders” (Andrews and Slade, 2001; Kessler and
Mroczek, 1992).

The Distress Tolerance Scale is a 15-item measure that assesses
participants’ abilities to withstand and cope with emotional distress
(Simons and Gaher, 2005). Respondents rated personal attitudes to-
wards feelings of emotional distress on a 5-point scale, ranging from 1
(“strongly agree”) to 5 (“strongly disagree”), with higher ratings in-
dicating greater distress tolerance. A global mean score of distress tol-
erance was calculated. We considered the scale descriptors and fol-
lowed the cutoffs used for the CD-RISC, which was also a 5-point scale.
As such, scores were dichotomously recoded so that global mean scores
less than 4 indicated “low distress tolerance” and scores of 4-to-5 in-
dicated “high distress tolerance.”

Perceived social support was measured using the Multidimensional
Scale of Perceived Social Support (MSPSS, Zimet et al., 1988), in which
participants rated perceived emotional support using a 7-point Likert
scale ranging from 1 (“very strongly disagree”) to 7 (“very strongly
agree”). This measure includes three subscales assessing perceived
support quality from family, friends, and partners. Because mean scores
greater than 5 reflected responses indicating “mildly agree,” “strongly
agree,” and “very strongly agree,” each subscale mean scores were re-
coded so that scores 5 or greater referred to “high perceived social
support,” and scores below 5 were referred to as “low perceived social
support.”

Instrumental support was assessed through a 4-item subscale of the
Two-Way Social Support Scale (Shakespeare-Finch and Obst, 2011).
Participants indicated the extent of they received instrumental support
based on a 6-point Likert scale ranging from 0 (“not at all”) to 5 (“al-
ways”). Items were summed to create a total score with a possible range
of 0 to 20. Given scale descriptors, a cutoff score with a sum of 16 or
greater indicated “high instrumental support,” whereas scores lower
than 16 indicated “low instrumental support.”

Loneliness was measured using an adapted 3-item version of the
UCLA Loneliness Scale Short Form (Hughes et al., 2004). Participants
rated lack of companionship, feelings of being left out, and isolation
from others on a scale of 1-to-3, with 1 as “hardly ever,” 2 as “some of
the time,” and 3 as “often.” A sum score for loneliness was calculated
with a total possible range of 3 to 9 and recoded dichotomously; a
cutoff score of 6 or greater indicated “high loneliness” as used in prior
studies (Lowthian et al., 2016; Tymoszuk et al., 2019).

Severity of COVID-19 pandemic-related worry was assessed using a
newly developed measure consisting of 6 items, which included the
following concerns: “Having enough groceries during city lockdowns/
social distancing protocols”, “obtaining a COVID-19 test if I become
sick”, “getting treated for COVID-19 if I contract it”, “keeping in touch
with loved ones during social distancing protocols”, “maintaining em-
ployment during the subsequent economic downturn”, and “having
enough money to pay for rent and buy basic necessities.” Participants
were asked to indicate their level of worry for each item on a scale of 1
to 5, with 1 being “not worried at all,” and 5 being “very worried.” Sum
scores were calculated with a total possible range of 6 to 30 and re-
coded into a dichotomous variable with a cutoff score of 24 or greater
as “highly worried.” Cronbach’s alpha for measure items was .70,

C.H. Liu, et al. Psychiatry Research 290 (2020) 113172

2

indicating good reliability.

2.2.2. Mental health outcomes
Depression was assessed with the 8-item version of the Patient

Health Questionnaire (PHQ-8, Kroenke et al., 2009) which assessed
frequency of depressive symptoms in the past two weeks on a scale of 0
(“not at all”) to 3 (“nearly every day”). Sum scores of the PHQ-8 had a
total possible range of 0 to 24 and were recoded dichotomously based
on a cutoff score of 10 or higher (Wu et al., 2019).

Anxiety was assessed with the Generalized Anxiety Disorder Scale
(GAD-7, Spitzer et al., 2006) a widely used measure assessing the fre-
quency of anxiety symptoms in the past two weeks on a scale of 0 to 3,
with 0 being “not at all” and 3 being “nearly every day.” Sum scores
ranged from 0 to 21. Following the convention of other studies
(Plummer et al., 2016), responses were recoded dichotomously based
on a cutoff score of 10 or higher to determine elevated anxiety.

The PTSD Checklist—Civilian Version (PCL-C), a validated 17-item
measure, was administered to assess PTSD symptoms (Weathers et al.,
1993). Participants indicated how much they were bothered by pro-
blems and experiences in response to stressful life events in the past
month, with 1 as “not at all” and 5 as “extremely.” Sum scores of the 17
items were calculated and created into a dichotomous variable with a
cutoff score of 45 or greater, based on the psychometric properties for
the measure and as suggested by the National Center for PTSD
(Blanchard et al., 1996).

2.2.3. Statistical analyses
The variables were normally distributed, with predictors indicating

acceptable levels of collinearity (VIF < 5). To identify potential risk
and protective factors of mental health symptoms, three logistic re-
gression models were performed to examine depression, anxiety, and
PTSD symptoms as primary outcomes. Resilience, distress tolerance,
perceived social support, instrumental social support, loneliness, and
COVID-19-specific worry were entered as predictors in unadjusted
models. Age, gender, income, and race were entered in each of the three
adjusted models. All variables were binary with exception to age and
income, which were continuous. Two-tailed p-values were used. To
guard against Type I error, Bonferroni-adjustments were made to con-
sider the 8 predictors and 4 covariates used in each model (.05/
12=.004). Our results and interpretations are therefore based on a
significance set at p<.004 (note that the significance in the tables re-
main unadjusted to provide more rather than less information to the
reader). All analyses were performed using SPSS 25.0.

3. Results

Table 1 shows demographic characteristics of our participants and
descriptive data on all predictors and outcomes. The sample was ra-
cially and ethnically diverse, with 59.6% White, 21.2% Asian, 5.3%
Black, 6.0% Hispanic/Latino, 0.1% AI/NA, 6.2% mixed race, and 1.4%
indicating another race. The majority of respondents were women
(81.3%), U.S.-born (86.3%), employed (66.7%), students (61.3%), and
those who earned less than $50,000 per year (82.1%). Among those
identifying as students, 89.7% were enrolled as full-time and 7.3% were
international students. Overall, participants scored as having high
loneliness (61.5%), low resilience (72.0%), and low distress tolerance
(74.1%). At the same time, the majority of respondents reported having
high levels of social support (family, partners, peer, and instrumental).
Finally, 43.3% of our sample had high levels of depression (PHQ-8
scores ≥ 10), 45.4% had high anxiety scores (GAD-7 scores ≥ 10) and
31.8% had high levels of PTSD symptoms (PCL-C scores ≥ 45).

Table 2 displays the associations between predictors and mental
health outcomes in each of the three models adjusted for the age,
gender, race, and income. The results described here pertain only to
significance set at p<.004 with Bonferroni corrections. Predictors that
were significantly associated with depression, anxiety, and PTSD

Table 1
Demographic characteristics and variable descriptives from Wave 1 of CARES
2020.

Factors Means (range) or %

Age (years) 24.5 (18.0 – 30.9)
18-21 28.6 %
22-26 34.7 %
26-30 36.6 %

Gender
Men 14.1 %
Women 81.3 %
Other gender 4.6 %

Race
White 59.6 %
Asian 21.2 %
Black 5.3 %
Hispanic or Latinx 6.0 %
American Indian/Native American 0.1 %
Mixed 6.2 %
Other 1.4 %

U.S.-born
Yes 86.3 %
No 13.7 %

Employed
Yes 66.7 %
No 33.3 %

Individual Income (USD/year)
No income 11.8 %
< $25,000 45.9 %
$25,000 – $49,999 24.4 %
$50,000 – $74,999 11.6 %
$75,000 – $99,999 2.6 %
$100,000 – $124,999 2.1 %
$125,000 – $149,999 0.3 %
$150,000 – $174,999 0.3 %
$175,000 – $199,999 0.6 %
$200,000 – $249,999 0.2 %
≥$250,000 0.2 %

Student
Yes 61.3 %
No 38.7 %

Student Enrollment Status (students only)
Full time 89.7 %
Part time 8.7 %
Other 1.6 %

International Student
Yes 7.3 %
No 92.7 %

Loneliness (LS-SF) 6.1 (3.0 – 9.0)
<6 38.5 %
≥6 61.5 %

COVID-19-specific worry 15.9 (6.0 – 30.0)
<24 89.9 %
≥24 10.1 %

Resilience (CD-RISC-10) 26.0 (4 – 40)
<30 72.0 %
≥30 28.0 %

Distress tolerance (DTS) 3.3 (1.0 – 5.0)
<4 74.1 %
≥4 25.9 %

Family social support (MSPSS) 5.1 (1.0 – 7.0)
<5 37.3 %
≥5 62.7 %

Partner social support (MSPSS) 5.6 (1.0 – 7.0)
<5 26.3 %
≥5 73.7 %

Peer social support (MSPSS) 5.7 (1.0 – 7.0)
<5 16.9 %
≥5 83.1 %

Instrumental social support (2-Way SSS) 16.6 (1.0 – 20.0)
<16 30.1 %
≥16 69.9 %

Depression (PHQ-8) 9.0 (0 – 24.0)
<10 56.7 %
≥10 43.3 %

Anxiety (GAD-7) 9.4 (0 – 21.0)
<10 54.6 %

(continued on next page)

C.H. Liu, et al. Psychiatry Research 290 (2020) 113172

3

included loneliness (OR range = 1.98 – 2.72), COVID-19-specific worry
(OR range = 2.87 – 5.05), and distress tolerance (OR range = 0.22 –
0.42). Specifically, those who endorsed high levels of loneliness and
worries about COVID-19 and low levels of distress tolerance were more
likely to score above the clinical cutoffs for depression, anxiety, and
PTSD. Those with high levels of resilience were less likely to score
above the cutoff for depression and anxiety. Those with high levels of
family support were less likely to score above the clinical cutoff for
depression and PTSD (OR = 0.46 and 0.44, respectively). Instrumental
support was negatively associated with depression. No associations
were obtained between support from partners and friends.

In analyses of associations between covariates and outcomes, age
and income were not associated with depression, anxiety, or PTSD.
With regard to gender, men who identified as transgender were more
likely to report high levels of PTSD (OR = 4.20, CI = 1.62 – 10.89,
p=.003); no differences were observed between men and women. Asian
Americans compared to Whites were less likely to report high levels of
depression (OR = 0.50, CI = 0.33 – 0.76, p=.001) and PTSD
(OR = 0.40, CI = 0.25 – 0.64, p<.001). Asians Americans and
Hispanic/Latinos were less likely to report high levels of anxiety
(OR = 0.35, CI = 0.24 – 0.53, p<.001, OR = 0.35, CI = 0.18 – 0.68,
p=.00, respectively).

4. Discussion

Our findings highlight major psychological challenges faced by

young adults during the initial weeks of the COVID-19 pandemic. At
least one-third of young adults reported having clinically elevated le-
vels of depression (43.3%), anxiety (45.4%), and PTSD symptoms
(31.8%). The rates of depression, anxiety, and PTSD in our study are
considerably higher compared to prior studies that have used the same
cut points (PHQ-8 ≥ 10; GAD-7 ≥ 10; and PCL-C ≥ 45). For instance,
PHQ-8 data collected from a study on U.S. adults in 2006 yielded a
prevalence of 6.2% among 18-24-year-olds and a prevalence of 13.1%
among 25-34-year-olds (Kroenke et al., 2009). Studies using the GAD-7
showed the following rates among similar groups: U.S. primary care
patients (23.0%; Spitzer et al., 2006), U.S. college students (21.0%;
Martin et al., 2014), and U.S. non-veteran community college students
(17.4%; Fortney et al., 2016). Finally, studies using a cutoff of ≥ 45 on
the PCL-C to assess PTSD in trauma survivors showed the following
rates: U.S. patients following hospital discharge from traumatic ortho-
pedic injury after one year (22.0%; Archer et al., 2016) and survivors
from the Wenchuan, China earthquake also after one year (26.3%;
Zhang et al., 2011). The high rates from our sample may reflect ongoing
distress, as we measured the symptoms in the weeks following the
government directives for closures. Young adults may have been par-
ticularly distressed in managing school or work responsibilities during
this time while having no sense of certainty regarding the pandemic’s
end. As well, the high rate of mental health concerns among study
participants may be partially attributable to the specific characteristics
of our sample; given that the study was launched on the East Coast, our
young adult respondents may have been located at pandemic “hot
spots,” with proximity to a greater number of COVID-19 cases poten-
tially being an added stressor for our sample.

Strikingly, the majority of respondents reported feeling lonely
during the first two months of the pandemic, as well as having low
resilience and low ability to tolerate distress. However, the majority
reported having social support from family, partners, and peers, as well
as instrumental support during this time. We note that the absolute
rates of low perceived social support seem problematic. For instance,
approximately 37% of respondents reported low family support. These

Table 1 (continued)

Factors Means (range) or %

≥10 45.4 %
PTSD (PCL-C) 38.3 (17.0 – 85.0)
<45 68.2 %
≥45 31.8 %

N = 898

Table 2
Odds ratios and confidence intervals for mental health outcomes from Wave 1 of CARES 2020.

Factors PHQ-8 – DepressionAdjusted ORa(95% CI) GAD-7 – AnxietyAdjusted ORa(95% CI) PTSD AdjustedAdjusted ORa(95% CI)

Loneliness (LS-SF)
<6 1.0 1.0 1.0
≥6 2.72 (1.92 – 3.87) ⁎⁎⁎ 1.98 (1.41 – 2.77) ⁎⁎⁎ 2.31 (1.55 – 3.43) ⁎⁎⁎

COVID-19-specific worry
<24 1.0 1.0 1.0
≥24 2.87 (1.67 – 4.94) ⁎⁎⁎ 4.12 (2.33 – 7.29) ⁎⁎⁎ 5.05 (2.92 – 874) ⁎⁎⁎

Resilience (CD-RISC-10)
<30 1.0 1.0 1.0
≥30 0.56 (0.38 – 0.83) ⁎⁎ 0.44 (0.30 – 0.64) ⁎⁎⁎ 0.70 (0.46 – 1.07)

Distress tolerance (DTS)
<4 1.0 1.0 1.0
≥4 0.36 (0.24 – 0.54) ⁎⁎⁎ 0.42 (0.28 – 0.62) ⁎⁎⁎ 0.22 (0.13 – 0.37) ⁎⁎⁎

Family social support (MSPSS)
<5 1.0 1.0 1.0
≥5 0.46 (0.32 – 0.66) ⁎⁎⁎ 0.64 (0.44 – 0.91)* 0.44 (0.30 – 0.64)⁎⁎⁎

Partner social support (MSPSS)
<5 1.0 1.0 1.0
≥5 1.26 (0.84 – 1.88) 1.32 (0.89 – 1.96) 1.00 (0.66 – 1.52)

Peer social support (MSPSS)
<5 1.0 1.0 1.0
≥5 1.05 (0.68 – 1.62) 1.27 (0.83 – 1.96) 0.88 (0.56 – 1.39)

Instrumental social support (2-Way SSS)
<16 1.0 1.0 1.0
≥16 0.60 (0.41 – 0.86)⁎⁎ 0.67 (0.46 – 0.96)* 0.63 (0.43 – 0.93)*

N = 898
⁎ p<.05
⁎⁎ p<.01
⁎⁎⁎ p<.001 (two-tailed, without Bonferroni adjustment),
a Adjusted covariates include age, race, gender, individual income

C.H. Liu, et al. Psychiatry Research 290 (2020) 113172

4

findings highlight major psychological challenges currently faced by
young adults during the initial weeks of the COVID-19 pandemic.

Our study also identified factors associated with clinical levels of
depression, anxiety, and PTSD symptoms. High loneliness and low
distress tolerance levels were consistently associated with high levels of
depression, anxiety, and PTSD. High levels of resilience were associated
with low anxiety. Social support from family was associated with low
levels of depression and PTSD symptoms, whereas support from part-
ners or friends was not associated with any mental health outcomes.
High levels of instrumental support were associated with low levels of
depression.

Our data is consistent with findings demonstrating loneliness as a
risk factor for mental health (Banerjee et al., 2020; Hawkley and
Cacioppo, 2010; Okruszek et al., 2020); this is particularly salient with
government directives for social distancing and isolation. Feeling cut off
from social groups may lead one to feel vulnerable and pessimistic
about one’s circumstances, altogether producing negative mood states
and anxiety (Muyan et al., 2016) that are further heightened during a
pandemic. The high levels of reported loneliness in our sample and its
association with depression, anxiety, and PTSD symptoms underscore
the severity of experiences of young adults during the pandemic.

Distress tolerance, or one’s ability to manage and tolerate emotional
distress, was strongly associated low levels of depressive and anxiety,
and PTSD symptoms; individual resilience was associated with low le-
vels of depression and anxiety symptoms, but not PTSD. Individual
resilience, which encompasses personal competence and trust in one’s
instincts (Connor and Davidson, 2003), has been associated with low
levels of depression, anxiety, and PTSD symptomatology after disasters
(Blackmon et al., 2017). One’s perceived ability to tolerate negative or
aversive emotional and/or physical states may be more protective than
the personal qualities that comprise psychological resilience, especially
for those experiencing symptoms of PTSD during a pandemic. The
pandemic is worldwide stressor without a foreseeable endpoint, and the
effects of the pandemic cannot be controlled by a single individual.
Furthermore, the pandemic simultaneously impacts various domains
(e.g., financial, relational, and health) with this stress potentially ex-
acerbating the sensations associated with PTSD symptoms. As such,
psychological resilience that is typically associated with overcoming
setbacks may not be sufficient for protecting against PTSD symptoms
within the first several weeks of a widespread pandemic. Interventions
that target distress tolerance, such as mindfulness-based interventions,
may be more effective than cognitive interventions targeting core be-
liefs about the self especially for those with PTSD symptoms (Nila et al.,
2016). Longitudinal approaches would help to examine this possibility
further.

Emotional support from family but not from friends and significant
others was associated with low levels of depression and PTSD. Friends
and significant others may have or are perceived to have less capacity
to validate other’s emotional experiences during a pandemic, con-
sidering that they may be young adults who are experiencing similar
struggles. Emotional support provided by family may be more stable
and coupled with the provision of material resources that young adults
may still receive from parents. Our findings are consistent with prior
work showing that family support but not friend and partner support
mediates the effects of stress on health (Lee et al., 2018). Family sup-
port may be more meaningful in providing reassurance to young adults,
considering the possible concrete needs during the pandemic.

Instrumental support, or tangible assistance, may be an important
factor for the mental health of young adults during the immediate
weeks of the COVID-19 pandemic onset given that many were faced
with acute disruptions, such as unemployment, financial stress, and
relocation following university campus closures. However, instru-
mental support was not significantly associated with any of the out-
comes after adjusting the p-value to .004. Additional research is needed
to clarify the respective roles on both emotional and instrument support
given variations in their potential effects on depression, anxiety, and

PTSD.
Our newly developed COVID-19-related worry measure uniquely

predicted mental health symptoms, underscoring how the specific fea-
tures of this pandemic give rise to acute stress. The stress resulting from
lifestyle changes due to features of COVID-19 itself may lead to greater
mental health concerns distinct from the endorsement of other risks.
Our analyses showed that the six items in our measure were reliable,
and the total subscale score was significantly associated with the
symptoms assessed in this study; however, additional work is required
to determine the validity of this measure.

In general, Asian Americans were less likely to report high levels of
mental health symptoms compared to Whites, with Hispanic/Latinx
respondents also being less likely to report high anxiety. Asian and
Latinx immigrants compared to those who are born in the U.S. are less
likely to endorse psychological distress (Dey and Lucas, 2006;
Takeuchi et al., 2007). It is possible that other experiences such as
ethnic identity, social networking, and family cohesion serve as a pro-
tective factor for mental health, especially for non-U.S.-born partici-
pants (Leong et al., 2013). The under-recognition of distress symptoms
may also be possible among ethnic minorities (Liu et al., 2020). Al-
though our sample size of gender minorities was small, men who
identified as transgender were more likely to report a high level of
PTSD symptoms, consistent with prior research (Reisner et al., 2016;
Shipherd et al., 2011). Greater attention to gender differences in mental
health symptoms as well as a deeper study regarding the specific ex-
periences faced by racial/ethnic and gender minorities during pan-
demic is warranted.

The cross-sectional design limits our ability to infer causality in-
volved in leading to mental health problems. We used a convenience
sample, and caution must be taken in the generalizability of our find-
ings to the broader population of young adults in the U.S. given the
uneven sampling of subgroups. The reliance of self-report itself has
limitations, such that it may be prone to misinterpretation. Future
analyses with the anticipated waves of data collection will enable us to
examine the association of our predictors to outcome measures of
mental health and to adjust for additional confounds. As well, we will
have an opportunity to examine potential moderation effects to un-
derstand whether outcomes vary by circumstances or individual char-
acteristics, such as socioeconomic capital, social support type, distress
tolerance, and resilience.

To our knowledge, our study is the first prospective cohort study to
assess mental health outcomes and risk and resilience factors in U.S.
young adults during the first several weeks of the COVID-19 pandemic.
In our study, one in three U.S. young adults reported clinical cut-off
symptoms of depression, anxiety, and PTSD as well as high levels of
loneliness. We present new evidence that signifies the roles of lone-
liness, distress tolerance, family support, and COVID-19-related worry
on mental health outcomes during the first month of the COVID-19
pandemic. Mental health interventions should incorporate these con-
structs to help mediate the impact of COVID-19 on adverse mental
health status among U.S. young adults.

CRediT authorship contribution statement

Cindy H. Liu: Conceptualization, Methodology, Formal analysis,
Investigation, Writing – original draft, Writing – review & editing,
Project administration, Supervision, Funding acquisition. Emily Zhang:
Data curation, Writing – original draft, Writing – review & editing,
Project administration. Ga Tin Fifi Wong: Data curation, Writing –
original draft, Project administration. Sunah Hyun: Writing – review &
editing. Hyeouk “Chris” Hahm: Conceptualization, Writing – review &
editing, Supervision, Funding acquisition.

Declaration of Competing Interest

There are no conflicts of interest to declare.

C.H. Liu, et al. Psychiatry Research 290 (2020) 113172

5

Acknowledgments

Support for this manuscript was provided through the National
Science Foundation (2027553) award (to C.H.L. and H.C.H.), a Mary A.
Tynan Faculty Fellowship and a NIMH K23 MH 107714-01 A1 award
(to C.H.L.), as well as a T32 MH 16259-39 award (to. S.H.).

Supplementary materials

Supplementary material associated with this article can be found, in
the online version, at doi:10.1016/j.psychres.2020.113172.

References

Andrews, G., Slade, T., 2001. Interpreting scores on the Kessler Psychological Distress
Scale (K10). Aust. New Zealand J. Public Health 25, 494–497. https://doi.org/10.
1111/j.1467-842X.2001.tb00310.x.

Archer, K.R., Heins, S.E., Abraham, C.M., Obremskey, W.T., Wegener, S.T., Castillo, R.C.,
2016. Clinical significance of pain at hospital discharge following traumatic ortho-
paedic injury: general health, depression, and PTSD outcomes at 1 year. Clin. J. Pain
32, 196–202. https://doi.org/10.1097/AJP.0000000000000246.

Banerjee, S., Burkholder, G., Sana, B., Szirony, M., 2020. Social Isolation as a predictor for
mortality: Implications for COVID-19 prognosis. medRxiv 2020.04.15.20066548.
https://doi.org/10.1101/2020.04.15.20066548.

Blackmon, B.J., Lee, J., Cochran, D.M., Kar, B., Rehner, T.A., Baker, A.M., 2017. Adapting
to life after hurricane Katrina and the deepwater horizon oil spill: an examination of
psychological resilience and depression on the Mississippi Gulf Coast. Social Work
Public Health 32, 65–76. https://doi.org/10.1080/19371918.2016.1188746.

Blanchard, E.B., Jones-Alexander, J., Buckley, T.C., Forneris, C.A., 1996. Psychometric
properties of the PTSD checklist (PCL). Behav. Res. Therapy 34, 669–673. https://
doi.org/10.1016/0005-7967(96)00033-2.

Blazer, D.G., Kessler, R.C., McGonagle, K.A., Swartz, M.S., 1994. The prevalence and
distribution of major depression in a national community sample: The National
Comorbidity Survey. Am. J. Psychiatry 151, 979–986. https://doi.org/10.1176/ajp.
151.7.979.

Breslau, N., Chilcoat, H.D., Kessler, R.C., Davis, G.C., 1999. Previous exposure to trauma
and PTSD effects of subsequent trauma: results from the detroit area survey of
trauma. AJP 156, 902–907. https://doi.org/10.1176/ajp.156.6.902.

Breslau, N., Peterson, E.L., Schultz, L.R., 2008. A second look at prior trauma and the
posttraumatic stress disorder effects of subsequent trauma: a prospective epidemio-
logical study. Arch. Gen. Psychiatry 65, 431–437. https://doi.org/10.1001/archpsyc.
65.4.431.

Brunet, A., Boyer, R., Weiss, D.S., Marmar, C.R., 2001. The effects of initial trauma ex-
posure on the symptomatic response to a subsequent trauma. Can. J. Behav. Sci. /
Revue canadienne des sciences du comportement 33, 97–102. https://doi.org/10.
1037/h0087132.

Chen, J.A., Stevens, C., Wong, S.H.M., Liu, C.H., 2019. Psychiatric symptoms and diag-
noses among U.S. college students: a comparison by race and ethnicity. Psychiatr.
Serv. 70, 442–449. https://doi.org/10.1176/appi.ps.201800388.

Cohen, J.R., Danielson, C.K., Adams, Z.W., Ruggiero, K.J., 2016. Distress tolerance and
social support in adolescence: predicting risk for internalizing and externalizing
symptoms following a natural disaster. J. Psychopathol. Behav. Assess. 38, 538–546.
https://doi.org/10.1007/s10862-016-9545-y.

Connor, K.M., Davidson, J.R.T., 2003. Development of a new resilience scale: the Connor-
Davidson Resilience Scale (CD-RISC). Depression Anxiety 18, 76–82. https://doi.org/
10.1002/da.10113.

Conrad, R., 2020. Universities’ response to supporting mental health of college students
during the COVID-19 pandemic [WWW Document]. Psychiatric Times URL. https://
www.psychiatrictimes.com/article/universities%E2%80%99-response-supporting-
mental-health-college-students-during-covid-19-pandemic (accessed 4.26.20).

Costello, E.J., Erkanli, A., Fairbank, J.A., Angold, A., 2002. The prevalence of potentially
traumatic events in childhood and adolescence. J. Traumatic Stress 15, 99–112.
https://doi.org/10.1023/A:1014851823163.

Dey, A.N., Lucas, J.W., 2006. Physical and mental health characteristics of US-and for-
eign-born adults: United States, 1998–2003. Adv. Data 369, 1–19.

Domagala-Krecioch, A., Majerek, B., 2013. The issue of loneliness in the period of
“emerging adulthood.”. Eur. Scientif. J.

Eisenberg, D., Gollust, S.E., Golberstein, E., Hefner, J.L., 2007. Prevalence and correlates
of depression, anxiety, and suicidality among university students. Am. J.
Orthopsychiatry 77, 534–542. https://doi.org/10.1037/0002-9432.77.4.534.

Fortney, J.C., Curran, G.M., Hunt, J.B., Cheney, A.M., Lu, L., Valenstein, M., Eisenberg,
D., 2016. Prevalence of probable mental disorders and help-seeking behaviors among
veteran and non-veteran community college students. General Hospital Psychiatry
38, 99–104. https://doi.org/10.1016/j.genhosppsych.2015.09.007.

Hawkley, L.C., Cacioppo, J.T., 2010. Loneliness matters: a theoretical and empirical re-
view of consequences and mechanisms. Ann. Behav. Med. 40, 218–227. https://doi.
org/10.1007/s12160-010-9210-8.

Hughes, M.E., Waite, L.J., Hawkley, L.C., Cacioppo, J.T., 2004. A short scale for mea-
suring loneliness in large surveys: results from two population-based studies. Res.
Aging 26, 655–672. https://doi.org/10.1177/0164027504268574.

Kessler, R., Mroczek, D., 1992. An update of the development of mental health screening

scales for the US National Health Interview Study. University of Michigan, Survey
Research Center of the Institute for Social Research, Ann Arbor.

Kessler, R.C., Galea, S., Gruber, M.J., Sampson, N.A., Ursano, R.J., Wessely, S., 2008.
Trends in mental illness and suicidality after Hurricane Katrina. Mol. Psychiatry 13,
374–384. https://doi.org/10.1038/sj.mp.4002119.

Kroenke, K., Strine, T.W., Spitzer, R.L., Williams, J.B.W., Berry, J.T., Mokdad, A.H., 2009.
The PHQ-8 as a measure of current depression in the general population. J. Affect
Disord. 114, 163–173. https://doi.org/10.1016/j.jad.2008.06.026.

Kukihara, H., Yamawaki, N., Uchiyama, K., Arai, S., Horikawa, E., 2014. Trauma, de-
pression, and resilience of earthquake/tsunami/nuclear disaster survivors of Hirono,
Fukushima, Japan. Psychiatry Clin. Neurosci. 68, 524–533. https://doi.org/10.1111/
pcn.12159.

Lee, C.-Y.S., Goldstein, S.E., Dik, B.J., 2018. The relational context of social support in
young adults: links with stress and well-being. J. Adult Dev. 25, 25–36. https://doi.
org/10.1007/s10804-017-9271-z.

Leong, F., Park, Y.S., Kalibatseva, Z., 2013. Disentangling immigrant status in mental
health: psychological protective and risk factors among Latino and Asian American
immigrants. Am. J. Orthopsychiatry 83, 361–371. https://doi.org/10.1111/ajop.
12020.

Liu, C.H., Li, H., Wu, E., Tung, E.S., Hahm, H.C., 2020. Parent perceptions of mental
illness in Chinese American youth. Asian J. Psychiatry 47, 101857. https://doi.org/
10.1016/j.ajp.2019.101857.

Liu, C.H., Stevens, C., Wong, S.H.M., Yasui, M., Chen, J.A., 2019. The prevalence and
predictors of mental health diagnoses and suicide among U.S. college students:
Implications for addressing disparities in service use. Depression Anxiety 36, 8–17.
https://doi.org/10.1002/da.22830.

Lowthian, J.A., Lennox, A., Curtis, A., Dale, J., Browning, C., Smit, D.V., Wilson, G.,
O’Brien, D., Rosewarne, C., Boyd, L., Garner, C., Cameron, P., 2016. HOspitals and
patients WoRking in Unity (HOW R U?): protocol for a prospective feasibility study of
telephone peer support to improve older patients’ quality of life after emergency
department discharge. BMJ Open 6, e013179. https://doi.org/10.1136/bmjopen-
2016-013179.

Martin, R.J., Usdan, S., Cremeens, J., Vail-Smith, K., 2014. Disordered gambling and co-
morbidity of psychiatric disorders among college students: An examination of pro-
blem drinking, anxiety and depression. J. Gambl. Stud. 30, 321–333. https://doi.org/
10.1007/s10899-013-9367-8.

Mojtabai, R., Olfson, M., Han, B., 2016. National trends in the prevalence and treatment
of depression in adolescents and young adults. Pediatrics 138, e20161878.

Muyan, M., Chang, E.C., Jilani, Z., Yu, T., Lin, J., Hirsch, J.K., 2016. Loneliness and
negative affective conditions in adults: is there any room for hope in predicting an-
xiety and depressive symptoms? J. Psychol. 150, 333–341. https://doi.org/10.1080/
00223980.2015.1039474.

Nila, K., Holt, D.V., Ditzen, B., Aguilar-Raab, C., 2016. Mindfulness-based stress reduction
(MBSR) enhances distress tolerance and resilience through changes in mindfulness.
Mental Health Prevention 4, 36–41. https://doi.org/10.1016/j.mhp.2016.01.001.

Okruszek, L., Aniszewska-Stańczuk, A., Piejka, A., Wiśniewska, M., Żurek, K., 2020. Safe
but lonely? Loneliness Mental Health Symptoms COVID-19.

Plummer, F., Manea, L., Trepel, D., McMillan, D., 2016. Screening for anxiety disorders
with the GAD-7 and GAD-2: a systematic review and diagnostic metaanalysis. General
Hospital Psychiatry 39, 24–31. https://doi.org/10.1016/j.genhosppsych.2015.11.
005.

Reisner, S.L., White Hughto, J.M., Gamarel, K.E., Keuroghlian, A.S., Mizock, L.,
Pachankis, J.E., 2016. Discriminatory experiences associated with posttraumatic
stress disorder symptoms among transgender adults. J. Counsel. Psychol. 63, 509.

Reynolds, K., Pietrzak, R.H., Mackenzie, C.S., Chou, K.L., Sareen, J., 2016. Post-Traumatic
Stress Disorder Across the Adult Lifespan: Findings From a Nationally Representative
Survey. Am. J. Geriatric Psychiatry 24, 81–93. https://doi.org/10.1016/j.jagp.2015.
11.001.

Shakespeare-Finch, J., Obst, P.L., 2011. The development of the 2-way social support
scale: a measure of giving and receiving emotional and instrumental support. J. Pers.
Assess. 93, 483–490. https://doi.org/10.1080/00223891.2011.594124.

Shipherd, J.C., Maguen, S., Skidmore, W.C., Abramovitz, S.M., 2011. Potentially trau-
matic events in a transgender sample: frequency and associated symptoms.
Traumatology 17, 56–67. https://doi.org/10.1177/1534765610395614.

Simons, J.S., Gaher, R.M., 2005. The distress tolerance scale: development and validation
of a self-report measure. Motiv. Emot. 29, 83–102. https://doi.org/10.1007/s11031-
005-7955-3.

Spitzer, R.L., Kroenke, K., Williams, J.B.W., Löwe, B., 2006. A brief measure for assessing
generalized anxiety disorder: the GAD-7. Arch. Intern. Med. 166, 1092–1097.
https://doi.org/10.1001/archinte.166.10.1092.

Takeuchi, D.T., Zane, N., Hong, S., Chae, D.H., Gong, F., Gee, G.C., Walton, E., Sue, S.,
Alegría, M., 2007. Immigration-related factors and mental disorders among Asian
Americans. Am. J. Public Health 97, 84–90. https://doi.org/10.2105/AJPH.2006.
088401.

Tymoszuk, U., Perkins, R., Fancourt, D., Williamon, A., 2019. Cross-sectional and long-
itudinal associations between receptive arts engagement and loneliness among older
adults. Soc. Psychiatry Psychiatr. Epidemiol. https://doi.org/10.1007/s00127-019-
01764-0.

Vrana, S., Lauterbach, D., 1994. Prevalence of traumatic events and post-traumatic psy-
chological symptoms in a nonclinical sample of college students. J. Trauma Stress 7,
289–302. https://doi.org/10.1007/BF02102949.

Weathers, F.W., Litz, B.T., Herman, D.S., Huska, J.A., Keane, T.M., 1993. The PTSD
Checklist (PCL): Reliability, validity, and diagnostic utility, in: Annual Convention of
the International Society for Traumatic Stress Studies, San Antonio, TX. San
Antonio, TX.

Wu, Y., Levis, B., Riehm, K.E., Saadat, N., Levis, A.W., Azar, M., Rice, D.B., Boruff, J.,

C.H. Liu, et al. Psychiatry Research 290 (2020) 113172

6

Cuijpers, P., Gilbody, S., Ioannidis, J.P.A., Kloda, L.A., McMillan, D., Patten, S.B.,
Shrier, I., Ziegelstein, R.C., Akena, D.H., Arroll, B., Ayalon, L., Baradaran, H.R.,
Baron, M., Bombardier, C.H., Butterworth, P., Carter, G., Chagas, M.H., Chan, J.C.N.,
Cholera, R., Conwell, Y., Ginkel, J.M., de, M., Fann, J.R., Fischer, F.H., Fung, D.,
Gelaye, B., Goodyear-Smith, F., Greeno, C.G., Hall, B.J., Harrison, P.A., Härter, M.,
Hegerl, U., Hides, L., Hobfoll, S.E., Hudson, M., Hyphantis, T., Inagaki, M., Jetté, N.,
Khamseh, M.E., Kiely, K.M., Kwan, Y., Lamers, F., Liu, S.-I., Lotrakul, M., Loureiro,
S.R., Löwe, B., McGuire, A., Mohd-Sidik, S., Munhoz, T.N., Muramatsu, K., Osório,
F.L., Patel, V., Pence, B.W., Persoons, P., Picardi, A., Reuter, K., Rooney, A.G., Santos,
I.S., Shaaban, J., Sidebottom, A., Simning, A., Stafford, L., Sung, S., Tan, P.L.L.,

Turner, A., van Weert, H.C., White, J., Whooley, M.A., Winkley, K., Yamada, M.,
Benedetti, A., Thombs, B.D., 2019. Equivalency of the diagnostic accuracy of the
PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis.
Psychol. Med. 1–13. https://doi.org/10.1017/S0033291719001314.

Zhang, Z., Shi, Z., Wang, L., Liu, M., 2011. One year later: Mental health problems among
survivors in hard-hit areas of the Wenchuan earthquake. Public Health 125, 293–300.
https://doi.org/10.1016/j.puhe.2010.12.008.

Zimet, G.D., Dahlem, N.W., Zimet, S.G., Farley, G.K., 1988. The multidimensional scale of
perceived social support. J. Pers. Assess. 52, 30–41. https://doi.org/10.1207/
s15327752jpa5201_2.

C.H. Liu, et al. Psychiatry Research 290 (2020) 113172

7

  • Factors associated with depression, anxiety, and PTSD symptomatology during the COVID-19 pandemic: Clinical implications for U.S. young adult mental health
    • Introduction
    • Methods
      • Study population
      • Measures
        • Risk and protective factors
        • Mental health outcomes
        • Statistical analyses
    • Results
    • Discussion
    • CRediT authorship contribution statement
    • Declaration of Competing Interest
    • mk:H1_13
    • Acknowledgments
    • mk:H1_15
    • Supplementary materials
    • References
Place your order
(550 words)

Approximate price: $22

Calculate the price of your order

550 words
We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
Total price:
$26
The price is based on these factors:
Academic level
Number of pages
Urgency
Basic features
  • Free title page and bibliography
  • Unlimited revisions
  • Plagiarism-free guarantee
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Part-by-part delivery
  • Overnight delivery
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

Read more

Zero-plagiarism guarantee

Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

Read more

Free-revision policy

Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

Read more

Privacy policy

Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.

Read more

Fair-cooperation guarantee

By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.

Read more